High performance, flexible, and compact low-density parity-check (ldpc) code

ABSTRACT

Certain aspects of the present disclosure generally relate to techniques for puncturing of structured low-density parity-check (LDPC) codes. Certain aspects of the present disclosure generally relate to methods and apparatus for a high-performance, flexible, and compact LDPC code. Certain aspects can enable LDPC code designs to support large ranges of rates, blocklengths, and granularity, while being capable of fine incremental redundancy hybrid automatic repeat request (IR-HARQ) extension while maintaining good floor performance, a high-level of parallelism to deliver high throughout performance, and a low description complexity.

CROSS-REFERENCE TO RELATED APPLICATIONS & PRIORITY CLAIM

This application claims benefit of and priority to U.S. ProvisionalPatent Application Ser. No. 62/349,784, filed Jun. 14, 2016 (163764P1),and to U.S. Provisional Patent Application Ser. No. 62/374,514(164403P1), filed Aug. 12, 2016, which are herein incorporated byreference in their entirety for all applicable purposes.

TECHNICAL FIELD

Certain aspects of the technology discussed below generally relate tomethods and apparatus for a high-performance, flexible, and compactlow-density parity-check (LDPC) code. More particularly, certain aspectsprovide techniques for LDPC code designs for large ranges of code rates,blocklengths, and granularity, while being capable of fine incrementalredundancy hybrid automatic repeat request (IR-HARQ) extension andmaintaining good error floor performance, a high-level of parallelismfor high throughout performance, and a low description complexity.

INTRODUCTION

Wireless communication systems are widely deployed to provide varioustypes of communication content such as voice, video, data, messaging,broadcasts, and so on. These systems may employ multiple-accesstechnologies capable of supporting communication with multiple users bysharing available system resources (e.g., bandwidth and transmit power).Examples of such multiple-access systems include code division multipleaccess (CDMA) systems, time division synchronous CDMA (TD-SCDMA), timedivision multiple Access (TDMA) systems, frequency division multipleaccess (FDMA) systems, single-carrier FDMA (SC-FDMA) systems, orthogonalfrequency division multiple access (OFDMA) systems, long term evolution(LTE) systems, 3^(rd) Generation Partnership Project (3GPP) LTE systems,LTE Advanced (LTE-A) systems. These multiple access technologies havebeen adopted in various telecommunication standards to provide a commonprotocol that enables different wireless devices to communicate on amunicipal, national, regional, and even global level. An example of anemerging telecommunication standard is new radio (NR), for example, 5Gradio access. NR is a set of enhancements to the LTE mobile standardpromulgated by 3GPP. It is designed to better support mobile broadbandInternet access by improving spectral efficiency, lowering costs,improving services, making use of new spectrum, and better integratingwith other open standards using OFDMA with a cyclic prefix (CP) on thedownlink (DL) and on the uplink (UL) as well as support beamforming,multiple-input multiple-output (MIMO) antenna technology, and carrieraggregation.

Generally, a wireless multiple-access communication system cansimultaneously support communication for multiple wireless nodes. Eachnode communicates with one or more base stations (BSs) via transmissionson forward and reverse links. The forward link (or downlink) refers to acommunication link from BSs to nodes, and a reverse link (or uplink)refers to a communication link from nodes to base stations.Communication links may be established via a single-input single-output,multiple-input single-output, or a MIMO system.

In some examples, a wireless multiple-access communication system mayinclude a number of BSs, each simultaneously supporting communicationfor multiple communication devices, otherwise known as user equipment(UEs). In an LTE or LTE-A network, a set of one or more BSs may definean e NodeB (eNB). In other examples (e.g., in a next generation, NR, or5G network), a wireless multiple access communication system may includea number of distributed units (DUs) (e.g., edge units (EUs), edge nodes(ENs), radio heads (RHs), smart radio heads (SRHs), transmissionreception points (TRPs), etc.) in communication with a number of centralunits (CUs) (e.g., central nodes (CNs), access node controllers (ANCs),etc.), where a set of one or more DUs, in communication with a CU, maydefine an access node (e.g., a BS, a NR BS, a 5G BS, a NB, an eNB, NRNB, a 5G NB, an access point (AP),), a network node, a gNB, a TRP,etc.). A BS, AN, or DU may communicate with a UE or a set of UEs ondownlink channels (e.g., for transmissions from a BS or to a UE) anduplink channels (e.g., for transmissions from a UE to a BS, AN, or DU).

Binary values (e.g., ones and zeros), are used to represent andcommunicate various types of information, such as video, audio,statistical information, etc. Unfortunately, during storage,transmission, and/or processing of binary data errors may beunintentionally introduced; for example, a “1” may be changed to a “0”or vice versa.

Generally, in the case of data transmission, a receiver observes eachreceived bit in the presence of noise or distortion and only anindication of the bit's value is obtained. Under these circumstances,the observed values are interpreted as a source of “soft” bits. A softbit indicates a preferred estimate of the bit's value (e.g., a 1 or a 0)together with some indication of the reliability of that estimate. Whilethe number of errors may be relatively low, even a small number oferrors or level of distortion can result in the data being unusable or,in the case of transmission errors, may necessitate re-transmission ofthe data.

To provide a mechanism to check for errors and, in some cases, tocorrect errors, binary data can be coded to introduce carefully designedredundancy. Coding of a unit of data produces what is commonly referredto as a code word. Because of its redundancy, a code word will ofteninclude more bits than the input unit of data from which the code wordwas produced. Redundant bits are added by an encoder to the transmittedbit stream to create a code word. When signals arising from transmittedcode words are received or processed, the redundant information includedin the code word as observed in the signal can be used to identifyand/or correct errors in, or remove distortion from, the received signalin order to recover the original data unit. Such error checking and/orcorrecting can be implemented as part of a decoding process. In theabsence of errors, or in the case of correctable errors or distortion,decoding can be used to recover from the source data being processed,the original data unit that was encoded. In the case of unrecoverableerrors, the decoding process may produce some indication that theoriginal data cannot be fully recovered. Such indications of decodingfailure can initiate retransmission of the data.

As the use of fiber optic lines for data communication and the rate atwhich data can be read from and stored to data storage devices (e.g.,disk drives, tapes, etc.) increases, there is an increasing need forefficient use of data storage and transmission capacity and also for theability to encode and decode data at high rates.

BRIEF SUMMARY

The following summarizes some aspects of the present disclosure toprovide a basic understanding of the discussed technology. This summaryis not an extensive overview of all contemplated features of thedisclosure, and is intended neither to identify key or critical elementsof all aspects of the disclosure nor to delineate the scope of any orall aspects of the disclosure. Its sole purpose is to present someconcepts of one or more aspects of the disclosure in summary form as aprelude to the more detailed description that is presented later. Afterconsidering this discussion, and particularly after reading the sectionentitled “Detailed Description” one will understand how the features ofthis disclosure provide advantages that include improved communicationsbetween access points and stations in a wireless network.

While encoding efficiency and high data rates are important, for anencoding and/or decoding system to be practical for use in a wide rangeof devices (e.g., consumer devices), it is also important that theencoders and/or decoders can be implemented at reasonable cost.

Communication systems often need to operate at several different rates.Adjustable low-density parity-check (LDPC) codes can be used for simpleimplementation to provide coding and decoding at different rates. Forexample, higher-rate LDPC codes can be generated by puncturinglower-rate LDPC codes.

As the demand for mobile broadband access continues to increase, thereexists a need for further improvements in NR technology. Preferably,these improvements should be applicable to other multi-accesstechnologies and the telecommunication standards that employ thesetechnologies. One area for improvements is the area ofencoding/decoding, applicable to NR. For example, techniques for highperformance LDPC codes for NR are desirable.

Certain aspects of the present disclosure generally relate to methodsand apparatus for a high-performance, flexible, and compact low-densityparity-check (LDPC) code design. The LDPC code designs can support largeranges of code rates, blocklengths, and granularity, while being capableof fine incremental redundancy hybrid automatic repeat request (IR-HARQ)extension and maintaining good error floor performance, a high-level ofparallelism to deliver high throughput performance, and a lowdescription complexity.

In one aspect, a method is provided for wireless communications by atransmitting device. The method generally includes determining aplurality of transmission rate regions associated with a transmissionrate to be used for transmitting information bits. The transmittingdevice selects a family of lifted LDPC codes of a set of families oflifted LDPC codes for encoding information bits for each of thetransmission rate regions, encodes the information bits using at leastone lifted LDPC code from the selected family of lifted LDPC codes fortransmission in each respective transmission rate region to produce oneor more code words, and transmits the one or more code words over amedium.

In one aspect, an apparatus, such as a transmitting device, is providedfor wireless communications. The apparatus generally includes means fordetermining a plurality of transmission rate regions associated with atransmission rate to be used for transmitting information bits. Thetransmitting device includes means for selecting a family of lifted LDPCcodes of a set of families of lifted LDPC codes for encoding informationbits for each of the transmission rate regions, means for encoding theinformation bits using at least one lifted LDPC code from the selectedfamily of lifted LDPC codes for transmission in each respectivetransmission rate region to produce one or more code words, and meansfor transmitting the one or more code words over a medium.

In one aspect, an apparatus, such as a transmitting device, is providedfor wireless communications. The apparatus generally includes at leastone processor coupled with a memory. The at least one processordetermines a plurality of transmission rate regions associated with atransmission rate to be used for transmitting information bits. The atleast one processor also selects a family of lifted LDPC codes of a setof families of lifted LDPC codes for encoding information bits for eachof the transmission rate regions, and encodes the information bits usingat least one lifted LDPC code from the selected family of lifted LDPCcodes for transmission in each respective transmission rate region toproduce one or more code words. The transmitting device also includes atransmitter configured to transmit the one or more code words over amedium.

In one aspect, a computer readable medium is provided. The computerreadable medium has computer executable code stored thereon for wirelesscommunications by a transmitting device. The code generally includescode for determining a plurality of transmission rate regions associatedwith a transmission rate to be used for transmitting information bits.The code also includes code for selecting a family of lifted LDPC codesof a set of families of lifted LDPC codes for encoding information bitsfor each of the transmission rate regions, code for encoding theinformation bits using at least one lifted LDPC code from the selectedfamily of lifted LDPC codes for transmission in each respectivetransmission rate region to produce one or more code words, and code fortransmitting the one or more code words over a medium.

To the accomplishment of the foregoing and related ends, the one or moreaspects comprise the features hereinafter fully described andparticularly pointed out in the claims. The following description andthe annexed drawings set forth in detail certain illustrative featuresof the one or more aspects. These features are indicative, however, ofbut a few of the various ways in which the principles of various aspectsmay be employed, and this description is intended to include all suchaspects and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above-recited features of the presentdisclosure can be understood in detail, a more particular description,briefly summarized above, may be had by reference to aspects, some ofwhich are illustrated in the appended drawings. The appended drawingsillustrate only certain typical aspects of this disclosure, however, andare therefore not to be considered limiting of its scope, for thedescription may admit to other equally effective aspects.

FIG. 1 is a block diagram conceptually illustrating an example wirelesscommunications system, in accordance with certain aspects of the presentdisclosure.

FIG. 2 is a block diagram illustrating an example logical architectureof a distributed RAN, in accordance with certain aspects of the presentdisclosure.

FIG. 3 is a diagram illustrating an example physical architecture of adistributed RAN, in accordance with certain aspects of the presentdisclosure.

FIG. 4 is a block diagram conceptually illustrating a design of anexample base station (BS) and user equipment (UE), in accordance withcertain aspects of the present disclosure.

FIG. 5 is a diagram showing examples for implementing a communicationprotocol stack, in accordance with certain aspects of the presentdisclosure.

FIG. 6 illustrates an example of a downlink (DL)-centric subframe, inaccordance with certain aspects of the present disclosure.

FIG. 7 illustrates an example of an uplink (UL)-centric subframe, inaccordance with certain aspects of the present disclosure.

FIG. 8 is a graphical representation of an example low-densityparity-check (LDPC) code, in accordance with certain aspects of thepresent disclosure.

FIG. 8A is a matrix representation of the example LDPC code of FIG. 8,in accordance with certain aspects of the present disclosure.

FIG. 9 is a graphical representation of liftings of the LDPC code ofFIG. 8, in accordance with certain aspects of the present disclosure.

FIG. 10 is an integer representation of a matrix for a quasi-cyclic802.11 LDPC code, in accordance with certain aspects.

FIG. 11 is a simplified block diagram illustrating an example encoder,in accordance with certain aspects of the present disclosure.

FIG. 12 is a simplified block diagram illustrating an example decoder,in accordance with certain aspects of the present disclosure.

FIG. 13 is a flow diagram illustrating example operations for encodingand transmitting a code word using a base graph structure that may beperformed by a transmitting device, in accordance with certain aspectsof the present disclosure.

FIG. 14 is a flow diagram illustrating example operations for encodingand transmitting a code word using a base graph structure that may beperformed by a transmitting device, in accordance with certain aspectsof the present disclosure.

FIG. 15 is a flow diagram illustrating example operations that may beperformed by a wireless device, according to aspects of the presentdisclosure.

FIG. 16 shows a structure of an example base parity check matrix (PCM),in accordance with aspects of the present disclosure.

FIG. 17 illustrates an exemplary optimized base graph, in accordancewith aspects of the present disclosure.

FIG. 18 is a table illustrating degree three checks and puncturing for ahigh rate code, in accordance with certain aspects of the presentdisclosure.

FIG. 18A is a table illustrating a core part of the PCM for theoptimized base graph of FIG. 17, used to get the table illustrated inFIG. 18, in accordance with certain aspects of the present disclosure.

FIG. 19 shows the core of an exemplary code family, in accordance withcertain aspects of the present disclosure.

FIG. 19A is a table illustrating the row degrees of the shortenedsubmatrix of the core illustrated in FIG. 19, in accordance with certainaspects of the present disclosure.

FIG. 20 shows the core of another exemplary code family, in accordancewith certain aspects of the present disclosure.

FIG. 20A is a table illustrating the row degrees of the shortenedsubmatrix of the core illustrated in FIG. 20, in accordance with certainaspects of the present disclosure.

FIG. 21 shows the core of yet another exemplary code family, inaccordance with certain aspects of the present disclosure.

FIG. 21A is a table illustrating the row degrees of the shortenedsubmatrix of the core illustrated in FIG. 21, in accordance with certainaspects of the present disclosure.

FIG. 22 is a table illustrating degree three checks and puncturing for amedium rate code, in accordance with certain aspects of the presentdisclosure.

FIG. 22A is a table illustrating the core part of the PCM, having alifting size value of 8, used to get the table illustrated in FIG. 22,in accordance with certain aspects of the present disclosure.

FIG. 23 is a table illustrating degree three checks and puncturing for alow rate code, in accordance with certain aspects of the presentdisclosure.

FIG. 23A is a table illustrating the core part of the PCM, having alifting size value of 8, used to get the table illustrated in FIG. 23,in accordance with certain aspects of the present disclosure.

FIG. 24 is a flow diagram illustrating example operations for selectinga family of LDPC codes to use for encoding information by a transmittingdevice, in accordance with certain aspects of the present disclosure.

FIG. 25 is a flow diagram illustrating example operations for wirelesscommunications by a transmitting device, in accordance with certainaspects of the present disclosure.

FIG. 26 is an example core lifted PCM with a lifting size value of 8, inaccordance with certain aspects of the present disclosure.

FIG. 27 is an example of the core lifted PCM illustrated in FIG. 25 witha single edge removed, in accordance with certain aspects of the presentdisclosure.

To facilitate understanding, identical reference numerals have beenused, where possible, to designate identical elements that are common tothe figures. It is contemplated that elements disclosed in oneembodiment may be beneficially utilized on other embodiments withoutspecific recitation.

DETAILED DESCRIPTION

Aspects of the present disclosure provide apparatus, methods, processingsystems, and computer program products for encoding (and/or decoding)for new radio (NR) access technology (e.g., 5G radio access). NR mayrefer to radios configured to operate according to a new air interfaceor fixed transport layer. NR may include support for enhanced mobilebroadband (eMBB) service targeting wide bandwidth (e.g., 80 MHz andbeyond), millimeter wave (mmW) service targeting high carrier frequency(e.g., 60 GHz), massive machine type communications (mMTC) servicetargeting non-backward compatible MTC techniques, and/or missioncritical (MiCr) service targeting ultra-reliable low-latencycommunications (URLLC) service. These services may include latency andreliability requirements. NR may use low-density parity-check (LDPC)coding and/or polar codes.

Certain aspects of the present disclosure generally relate to methodsand apparatus for encoding and/or decoding using LDPC code designs thatmay be high-performance, flexible, and compact. The LDPC code designsmay support large ranges of code rates, blocklengths, and granularity.The LDPC code designs may support fine incremental redundancy hybridautomatic repeat request (IR-HARQ) extension. The LDPC code designs mayhave a good floor performance, a high level of parallelism to deliverhigh throughput performance, and a low description complexity.

Various aspects of the disclosure are described more fully hereinafterwith reference to the accompanying drawings. This disclosure may,however, be embodied in many different forms and should not be construedas limited to any specific structure or function presented throughoutthis disclosure. Rather, these aspects are provided so that thisdisclosure will be thorough and complete, and will fully convey thescope of the disclosure to those skilled in the art. Based on theteachings herein one skilled in the art should appreciate that the scopeof the disclosure is intended to cover any aspect of the disclosuredisclosed herein, whether implemented independently of or combined withany other aspect of the disclosure. For example, an apparatus may beimplemented or a method may be practiced using any number of the aspectsset forth herein. In addition, the scope of the disclosure is intendedto cover such an apparatus or method, which is practiced using otherstructure, functionality, or structure and functionality in addition toor other than the various aspects of the disclosure set forth herein. Itshould be understood that any aspect of the disclosure disclosed hereinmay be embodied by one or more elements of a claim. The word “exemplary”is used herein to mean “serving as an example, instance, orillustration.” Any aspect described herein as “exemplary” is notnecessarily to be construed as preferred or advantageous over otheraspects.

Although particular aspects are described herein, many variations andpermutations of these aspects fall within the scope of the disclosure.Although some benefits and advantages of the preferred aspects arementioned, the scope of the disclosure is not intended to be limited toparticular benefits, uses, or objectives. Rather, aspects of thedisclosure are intended to be broadly applicable to different wirelesstechnologies, system configurations, networks, and transmissionprotocols, some of which are illustrated by way of example in thefigures and in the following description of the preferred aspects. Thedetailed description and drawings are merely illustrative of thedisclosure rather than limiting, the scope of the disclosure beingdefined by the appended claims and equivalents thereof.

The techniques described herein may be used for various wirelesscommunication networks such as Long Term Evolution (LTE), Code DivisionMultiple Access (CDMA) networks, Time Division Multiple Access (TDMA)networks, Frequency Division Multiple Access (FDMA) networks, OrthogonalFDMA (OFDMA) networks, Single-Carrier FDMA (SC-FDMA) networks, etc. Theterms “networks” and “systems” are often used interchangeably. A CDMAnetwork may implement a radio technology such as Universal TerrestrialRadio Access (UTRA), CDMA2000, etc. UTRA includes Wideband-CDMA (W-CDMA)and Low Chip Rate (LCR). CDMA2000 covers IS-2000, IS-95, and IS-856standards. A TDMA network may implement a radio technology such asGlobal System for Mobile Communications (GSM). An OFDMA network mayimplement a radio technology such as NR (e.g., 5G RA), Evolved UTRA(E-UTRA), IEEE 802.11, IEEE 802.16, IEEE 802.20, Flash-OFDM®, etc. UTRA,E-UTRA, and GSM are part of Universal Mobile Telecommunication System(UMTS). 3GPP LTE and LTE-Advanced (LTE-A) are releases of UMTS that useE-UTRA. UTRA, E-UTRA, UMTS, LTE, LTE-A and GSM are described indocuments from an organization named “3rd Generation PartnershipProject” (3GPP). CDMA2000 is described in documents from an organizationnamed “3rd Generation Partnership Project 2” (3GPP2). NR is an emergingwireless communications technology under development in conjunction withthe 5G Technology Forum (5GTF). These communications networks are merelylisted as examples of networks in which the techniques described in thisdisclosure may be applied; however, this disclosure is not limited tothe above-described communications network.

For clarity, while aspects may be described herein using terminologycommonly associated with 3G and/or 4G wireless technologies, aspects ofthe present disclosure can be applied in other generation-basedcommunication systems, such as 5G and later, including NR technologies.

An Example Wireless Communication System

FIG. 1 illustrates an example wireless communications network 100 inwhich aspects of the present disclosure may be performed. Wirelesscommunications network 100 may be a new radio (NR) or 5G network.Wireless communications network 100 may include a transmitting devicesuch as a user equipment (UE) 120 or a base station (BS) 110. Thetransmitting device can encode a set of information bits based on alow-density parity-check (LDPC) code to produce a code word, the LDPCcode defined by a matrix having a first number of variable nodes and asecond number of check nodes. The LDPC code used by the transmittingdevice may be designed according to the LDPC code designs describedherein for high-performance, flexible, and compact LDPC code. The LPDCcode design may be used by the transmitting device to encode the set ofinformation bits, to support large ranges of code rates, blocklengths,and granularity.

As illustrated in FIG. 1, wireless communications network 100 mayinclude a number of BSs 110 and other network entities. A BS may be astation that communicates with UEs. Each BS 110 may providecommunication coverage for a particular geographic area. In 3GPP, theterm “cell” can refer to a coverage area of a Node B and/or a Node Bsubsystem serving this coverage area, depending on the context in whichthe term is used. In NR systems, the term “cell” and gNB, Node B, 5G NB,AP, NR BS, NR BS, TRP, etc., may be interchangeable. In some examples, acell may not necessarily be stationary, and the geographic area of thecell may move according to the location of a mobile BS. In someexamples, the BSs may be interconnected to one another and/or to one ormore other BSs or network nodes (not shown) in wireless communicationsnetwork 100 through various types of backhaul interfaces such as adirect physical connection, a virtual network, or the like using anysuitable transport network.

In general, any number of wireless networks may be deployed in a givengeographic area. Each wireless network may support a particular radioaccess technology (RAT) and may operate on one or more frequencies. ARAT may also be referred to as a radio technology, an air interface,etc. A frequency may also be referred to as a carrier, a frequencychannel, etc. Each frequency may support a single RAT in a givengeographic area in order to avoid interference between wireless networksof different RATs. In some cases, NR or 5G RAT networks may be deployed.

A BS may provide communication coverage for a macro cell, a pico cell, afemto cell, and/or other types of cell. A macro cell may cover arelatively large geographic area (e.g., several kilometers in radius)and may allow unrestricted access by UEs with service subscription. Apico cell may cover a relatively small geographic area and may allowunrestricted access by UEs with service subscription. A femto cell maycover a relatively small geographic area (e.g., a home) and may allowrestricted access by UEs having association with the femto cell (e.g.,UEs in a Closed Subscriber Group (CSG), UEs for users in the home,etc.). A BS for a macro cell may be referred to as a macro BS. A BS fora pico cell may be referred to as a pico BS. A BS for a femto cell maybe referred to as a femto BS or a home BS. In the example shown in FIG.1, BS 110 a, BS 110 b, and BS 110 c may be macro BSs for the macro cell102 a, macro cell 102 b, and macro cell 102 c, respectively. BS 110 xmay be a pico BS for pico cell 102 x. BS 110 y and BS 110 z may be femtoBS for the femto cell 102 y and femto cell 102 z, respectively. A BS maysupport one or multiple (e.g., three) cells.

Wireless communications network 100 may also include relay stations. Arelay station is a station that receives a transmission of data and/orother information from an upstream station (e.g., a BS 110 or a UE 120)and sends a transmission of the data and/or other information to adownstream station (e.g., a UE 120 or a BS 110). A relay station mayalso be a UE that relays transmissions for other UEs. In the exampleshown in FIG. 1, relay station 110 r may communicate with BS 110 a andUE 120 r in order to facilitate communication between BS 110 a and UE120 r. A relay station may also be referred to as a relay, a relay eNB,etc.

Wireless communications network 100 may be a heterogeneous network thatincludes BSs of different types, for example, macro BS, pico BS, femtoBS, relays, etc. These different types of BSs may have differenttransmit power levels, different coverage areas, and different impact oninterference in the wireless communications network 100. For example, amacro BS may have a high transmit power level (e.g., 20 Watts) whereaspico BS, femto BS, and relays may have a lower transmit power level(e.g., 1 Watt).

Wireless communications network 100 may support synchronous orasynchronous operation. For synchronous operation, the BSs may havesimilar frame timing, and transmissions from different BSs may beapproximately aligned in time. For asynchronous operation, the BSs mayhave different frame timing, and transmissions from different BSs maynot be aligned in time. The techniques described herein may be used forboth synchronous and asynchronous operation.

Network controller 130 may couple to a set of BSs and providecoordination and control for these BSs. Network controller 130 maycommunicate with BSs 110 via a backhaul. BSs 110 may also communicatewith one another, e.g., directly or indirectly via wireless or wirelinebackhaul.

UEs 120 (e.g., UE 120 x, UE 120 y, etc.) may be dispersed throughoutwireless communications network 100, and each UE may be stationary ormobile. A UE may also be referred to as a mobile station, a terminal, anaccess terminal, a subscriber unit, a station, a Customer PremisesEquipment (CPE), a cellular phone, a smart phone, a personal digitalassistant (PDA), a wireless modem, a wireless communication device, ahandheld device, a laptop computer, a cordless phone, a wireless localloop (WLL) station, a tablet, a camera, a gaming device, a netbook, asmartbook, an ultrabook, a medical device or medical equipment, abiometric sensor/device, a wearable device such as a smart watch, smartclothing, smart glasses, a smart wrist band, smart jewelry (e.g., asmart ring, a smart bracelet, etc.), an entertainment device (e.g., amusic device, a video device, a satellite radio, etc.), a vehicularcomponent or sensor, a smart meter/sensor, industrial manufacturingequipment, a global positioning system device, or any other suitabledevice that is configured to communicate via a wireless or wired medium.Some UEs may be considered evolved or machine-type communication (MTC)devices or evolved MTC (eMTC) devices. MTC and eMTC UEs include, forexample, robots, drones, remote devices, sensors, meters, monitors,location tags, etc., that may communicate with a BS, another device(e.g., remote device), or some other entity. A wireless node mayprovide, for example, connectivity for or to a network (e.g., a widearea network such as Internet or a cellular network) via a wired orwireless communication link. Some UEs may be consideredInternet-of-Things (IoT) devices.

In FIG. 1, a solid line with double arrows indicates desiredtransmissions between a UE and a serving BS, which is a BS designated toserve the UE on the downlink and/or uplink. A finely dashed line withdouble arrows indicates interfering transmissions between a UE and a BS.

Certain wireless networks (e.g., LTE) utilize orthogonal frequencydivision multiplexing (OFDM) on the downlink and single-carrierfrequency division multiplexing (SC-FDM) on the uplink. OFDM and SC-FDMpartition the system bandwidth into multiple (K) orthogonal subcarriers,which are also commonly referred to as tones, bins, etc. Each subcarriermay be modulated with data. In general, modulation symbols are sent inthe frequency domain with OFDM and in the time domain with SC-FDM. Thespacing between adjacent subcarriers may be fixed, and the total numberof subcarriers (K) may be dependent on the system bandwidth. Forexample, the spacing of the subcarriers may be 15 kHz and the minimumresource allocation (called a “resource block” (RB)) may be 12subcarriers (i.e., 180 kHz). Consequently, the nominal Fast FourierTransform (FFT) size may be equal to 128, 256, 512, 1024 or 2048 forsystem bandwidth of 1.25 MHz, 2.5 MHz, 5 MHz, 10 MHz, or 20 MHz,respectively. The system bandwidth may also be partitioned intosubbands. For example, a subband may cover 1.08 MHz (i.e., 6 RBs), andthere may be 1, 2, 4, 8 or 16 subbands for system bandwidth of 1.25 MHz,2.5 MHz, 5 MHz, 10 MHz, or 20 MHz, respectively.

NR may utilize OFDM with a CP on the uplink and downlink and includesupport for half-duplex operation using TDD. A single component carrierbandwidth of 100 MHz may be supported. NR RBs may span 12 subcarrierswith a subcarrier bandwidth of 75 kHz over a 0.1 ms duration. Each radioframe may consist of 50 subframes with a length of 10 ms. Consequently,each subframe may have a length of 0.2 ms. Each subframe may indicate alink direction (i.e., downlink or uplink) for data transmission and thelink direction for each subframe may be dynamically switched. Eachsubframe may include DL/UL data as well as DL/UL control data. UL and DLsubframes for NR may be as described in more detail below with respectto FIGS. 6 and 7. Beamforming may be supported and beam direction may bedynamically configured. MIMO transmissions with precoding may also besupported. MIMO configurations in the DL may support up to 8 transmitantennas with multi-layer DL transmissions up to 8 streams and up to 2streams per UE. Multi-layer transmissions with up to 2 streams per UEmay be supported. Aggregation of multiple cells may be supported with upto 8 serving cells. Alternatively, NR may support a different airinterface, other than an OFDM-based.

In some examples, access to the air interface may be scheduled. Forexample, a scheduling entity (e.g., a BS 110 or UE 120) allocatesresources for communication among some or all devices and equipmentwithin its service area or cell. Within the present disclosure, asdiscussed further below, the scheduling entity may be responsible forscheduling, assigning, reconfiguring, and releasing resources for one ormore subordinate entities. That is, for scheduled communication,subordinate entities utilize resources allocated by the schedulingentity. BSs are not the only entities that may function as a schedulingentity. That is, in some examples, a UE may function as a schedulingentity, scheduling resources for one or more subordinate entities (e.g.,one or more other UEs). In this example, the UE is functioning as ascheduling entity, and other UEs utilize resources scheduled by the UEfor wireless communication. A UE may function as a scheduling entity ina peer-to-peer (P2P) network, and/or in a mesh network. In a meshnetwork example, UEs may optionally communicate directly with oneanother in addition to communicating with the scheduling entity.

Thus, in a wireless communication network with a scheduled access totime-frequency resources and having a cellular configuration, a P2Pconfiguration, and a mesh configuration, a scheduling entity and one ormore subordinate entities may communicate utilizing the scheduledresources.

The NR radio access network (RAN) may include one or more central units(CU) and distributed units (DUs). A NR BS (e.g., a gNB, a 5G NB, a NB, a5G NB, a TRP, an AP) may correspond to one or multiple BSs. NR cells canbe configured as access cells (ACells) or data only cells (DCells).DCells may be cells used for carrier aggregation or dual connectivity,but not used for initial access, cell selection/reselection, orhandover.

FIG. 2 illustrates an example logical architecture of a distributed RAN200, which may be implemented in wireless communications system 100illustrated in FIG. 1. 5G access node (AN) 206 may include access nodecontroller (ANC) 202. ANC 202 may be a CU of distributed RAN 200. Abackhaul interface to next generation core network (NG-CN) 204 mayterminate at ANC 202. A backhaul interface to neighboring nextgeneration access nodes (NG-ANs) may terminate at ANC 202. ANC 202 mayinclude one or more TRPs 208.

TRPs 208 comprise DUs. TRPs 208 may be connected to one ANC (ANC 202) ormore than one ANC (not illustrated). For example, for RAN sharing, radioas a service (RaaS), and service specific AND deployments, the TRP maybe connected to more than one ANC 202. A TRP 208 may include one or moreantenna ports. TRPs 208 may be configured to individually (e.g., dynamicselection) or jointly (e.g., joint transmission) serve traffic to a UE(e.g., a UE 120).

Example logical architecture of the distributed RAN 200 may be used toillustrate fronthaul definition. The logical architecture may supportfronthauling solutions across different deployment types. For example,the logical architecture may be based on transmit network capabilities(e.g., bandwidth, latency, and/or jitter). The logical architecture mayshare features and/or components with LTE. NG-AN 210 may support dualconnectivity with NR. NG-AN 210 may share a common fronthaul for LTE andNR. The logical architecture may enable cooperation between and amongTRPs 208. For example, cooperation may be pre-configured within a TRP208 and/or across TRPs 208 via ANC 202. There may be no inter-TRPinterface.

The logical architecture for distributed RAN 200 may include a dynamicconfiguration of split logical functions. As will be described in moredetail with reference to FIG. 5, the Radio Resource Control (RRC) layer,Packet Data Convergence Protocol (PDCP) layer, Radio Link Control (RLC)layer, Medium Access Control (MAC) layer, and a Physical (PHY) layersmay be placed at the DU (e.g., a TRP 208) or the CU (e.g., ANC 202).

FIG. 3 illustrates an example physical architecture of a distributed RAN300, according to aspects of the present disclosure. As shown in FIG. 3,distributed RAN 300 includes centralized core network unit (C-CU) 302,centralized RAN unit (C-RU) 304, and DU 306.

C-CU 302 may host core network functions. C-CU 302 may be centrallydeployed. C-CU 302 functionality may be offloaded (e.g., to advancedwireless services (AWS)), in an effort to handle peak capacity. C-RU 304may host one or more ANC functions. Optionally, C-RU 304 may host corenetwork functions locally. C-RU 304 may have a distributed deployment.C-RU 304 may be located near an edge the network. DU 306 may host one ormore TRPs (edge node (EN), an edge unit (EU), a radio head (RH), a smartradio head (SRH), or the like). DU 306 may be located at edges of thenetwork with radio frequency (RF) functionality.

FIG. 4 illustrates example components of the BS 110 and the UE 120illustrated in FIG. 1, which may be used to implement aspects of thepresent disclosure for high performance, flexible, and compact LDPCcoding. One or more of the components of BS 110 and UE 120 illustratedin FIG. 4 may be used to practice aspects of the present disclosure. Forexample, antenna(s) 452 a-454 r, Demodulator(s)/Modulator(s) 454 a-454r, TX MIMO processor 466, Receive Processor 458, Transmit Processor 464,and/or Controller/Processor 480 of UE 120 and/or antenna(s) 434 a 434 t,Demodulator(s)/Modulator(s) 432 a-434 t, TX MIMO Processors 430,Transmit Processor 420, Receive Processor 438, and/orController/Processor 440 of BS 110 may be used to perform the operations1300-1500, 2400, and 2500 described herein and illustrated withreference to FIGS. 13-15, 24, and 25, respectively.

For a restricted association scenario, BS 110 may be macro BS 110 c inFIG. 1, and UE 120 may be UE 120 y. BS 110 may also be a BS of someother type. BS 110 may be equipped with antennas 434 a through 434 t andUE 120 may be equipped with antennas 452 a through 452 r.

At BS 110, transmit processor 420 may receive data from data source 412and control information from controller/processor 440. The controlinformation may be for the Physical Broadcast Channel (PBCH), PhysicalControl Format Indicator Channel (PCFICH), Physical Hybrid ARQ IndicatorChannel (PHICH), Physical Downlink Control Channel (PDCCH), or othercontrol channel or signal. The data may be for the Physical DownlinkShared Channel (PDSCH), or other data channel or signal. Transmitprocessor 420 may process (e.g., encode and symbol map) the data andcontrol information to obtain data symbols and control symbols,respectively. For example, transmit processor 420 may encode theinformation bits using LPDC code designs discussed in greater detailbelow. Transmit processor 420 may also generate reference symbols, forexample, for the primary synchronization signal (PSS), secondarysynchronization signal (SSS), and cell-specific reference signal (CRS).Transmit (TX) multiple-input multiple-output (MIMO) processor 430 mayperform spatial processing (e.g., precoding) on the data symbols, thecontrol symbols, and/or the reference symbols, if applicable, and mayprovide output symbol streams to the modulators (MODs) 432 a through 432t. Each modulator 432 may process a respective output symbol stream(e.g., for OFDM, etc.) to obtain an output sample stream. Each modulator432 may further process (e.g., convert to analog, amplify, filter, andupconvert) the output sample stream to obtain a downlink signal.Downlink signals from modulators 432 a through 432 t may be transmittedvia antennas 434 a through 434 t, respectively.

At UE 120, antennas 452 a through 452 r may receive the downlink signalsfrom BS 110 and may provide received signals to the demodulators(DEMODs) 454 a through 454 r, respectively. Each demodulator 454 maycondition (e.g., filter, amplify, downconvert, and digitize) arespective received signal to obtain input samples. Each demodulator 454may further process the input samples (e.g., for OFDM, etc.) to obtainreceived symbols. MIMO detector 456 may obtain received symbols from allthe demodulators 454 a through 454 r, perform MIMO detection on thereceived symbols if applicable, and provide detected symbols. Receiveprocessor 458 may process (e.g., demodulate, deinterleave, and decode)the detected symbols, provide decoded data for UE 120 to a data sink460, and provide decoded control information to controller/processor480.

On the uplink, at UE 120, transmit processor 464 may receive and processdata (e.g., for the Physical Uplink Shared Channel (PUSCH) or other datachannel or signal) from data source 462 and control information (e.g.,for the Physical Uplink Control Channel (PUCCH) or other control channelor signal) from controller/processor 480. Transmit processor 464 mayalso generate reference symbols for a reference signal. The symbols fromtransmit processor 464 may be precoded by TX MIMO processor 466 ifapplicable, further processed by demodulators 454 a through 454 r (e.g.,for SC-FDM, etc.), and transmitted to BS 110. At BS 110, the uplinksignals from the UE 120 may be received by antennas 434, processed bymodulators 432, detected by MIMO detector 436 if applicable, and furtherprocessed by receive processor 438 to obtain decoded data and controlinformation sent by UE 120. Receive processor 438 may provide thedecoded data to data sink 439 and the decoded control information tocontroller/processor 440.

Memory 442 may store data and program codes for BS 110 and memory 482may store data and program codes for UE 120. Scheduler 444 may scheduleUEs for data transmission on the downlink and/or uplink.

FIG. 5 illustrates a diagram 500 showing examples for implementing acommunications protocol stack, according to aspects of the presentdisclosure. The illustrated communications protocol stacks may beimplemented by devices operating in a in a 5G system (e.g., a systemthat supports uplink-based mobility). Diagram 500 illustrates acommunications protocol stack including RRC layer 510, PDCP layer 515,RLC layer 520, MAC layer 525, and PHY layer 530. In an example, thelayers of a protocol stack may be implemented as separate modules ofsoftware, portions of a processor or ASIC, portions of non-collocateddevices connected by a communications link, or various combinationsthereof. Collocated and non-collocated implementations may be used, forexample, in a protocol stack for a network access device (e.g., ANs,CUs, and/or DUs) or a UE.

A first option 505-a shows a split implementation of a protocol stack,in which implementation of the protocol stack is split between acentralized network access device (e.g., ANC 202) and distributednetwork access device (e.g., DU 208). In the first option 505-a, RRClayer 510 and PDCP layer 515 may be implemented by the CU, and RLC layer520, MAC layer 525, and PHY layer 530 may be implemented by the DU. Invarious examples the CU and the DU may be collocated or non-collocated.The first option 505-a may be useful in a macro cell, micro cell, orpico cell deployment.

A second option 505-b shows a unified implementation of a protocolstack, in which the protocol stack is implemented in a single networkaccess device (e.g., access node (AN), NR BS, a NR NBa network node(NN), TRP, gNB, etc.). In the second option, RRC layer 510, PDCP layer515, RLC layer 520, MAC layer 525, and PHY layer 530 may each beimplemented by the AN. The second option 505-b may be useful in a femtocell deployment.

Regardless of whether a network access device implements part or all ofa protocol stack, a UE may implement the entire protocol stack (e.g.,RRC layer 510, PDCP layer 515, RLC layer 520, MAC layer 525, and PHYlayer 530).

FIG. 6 is a diagram showing an example of a DL-centric subframe 600. TheDL-centric subframe 600 may include control portion 602. Control portion602 may exist in the initial or beginning portion of DL-centric subframe600. Control portion 602 may include various scheduling informationand/or control information corresponding to various portions ofDL-centric subframe 600. In some configurations, control portion 602 maybe a physical DL control channel (PDCCH), as shown in FIG. 6. DL-centricsubframe 600 may also include DL data portion 604. DL data portion 604may be referred to as the payload of DL-centric subframe 600. DL dataportion 604 may include the communication resources utilized tocommunicate DL data from the scheduling entity (e.g., UE or BS) to thesubordinate entity (e.g., UE). In some configurations, DL data portion604 may be a physical DL shared channel (PDSCH).

DL-centric subframe 600 may also include common UL portion 606. CommonUL portion 606 may be referred to as an UL burst, a common UL burst,and/or various other suitable terms. Common UL portion 606 may includefeedback information corresponding to various other portions ofDL-centric subframe 600. For example, common UL portion 606 may includefeedback information corresponding to control portion 602. Non-limitingexamples of feedback information may include an acknowledgment (ACK)signal, a negative acknowledgment (NACK) signal, a HARQ indicator,and/or various other suitable types of information. Common UL portion606 may additionally or alternatively include information, such asinformation pertaining to random access channel (RACH) procedures,scheduling requests (SRs), and various other suitable types ofinformation. As illustrated in FIG. 6, the end of DL data portion 604may be separated in time from the beginning of common UL portion 606.This time separation may be referred to as a gap, a guard period, aguard interval, and/or various other suitable terms. This separationprovides time for the switch-over from DL communication (e.g., receptionoperation by the subordinate entity (e.g., UE)) to UL communication(e.g., transmission by the subordinate entity (e.g., UE)). The foregoingis merely one example of a DL-centric subframe and alternativestructures having similar features may exist without necessarilydeviating from the aspects described herein.

FIG. 7 is a diagram showing an example of an UL-centric subframe 700.UL-centric subframe 700 may include control portion 702. Control portion702 may exist in the initial or beginning portion of UL-centric subframe700. Control portion 702 in FIG. 7 may be similar to control portion 602described above with reference to FIG. 6. UL-centric subframe 700 mayalso include UL data portion 704. UL data portion 704 may be referred toas the payload of UL-centric subframe 700. UL data portion 704 may referto the communication resources utilized to communicate UL data from thesubordinate entity (e.g., UE) to the scheduling entity (e.g., UE or BS).In some configurations, control portion 702 may be a PDCCH.

As illustrated in FIG. 7, the end of control portion 702 may beseparated in time from the beginning of UL data portion 704. This timeseparation may be referred to as a gap, guard period, guard interval,and/or various other suitable terms. This separation provides time forthe switch-over from DL communication (e.g., reception operation by thescheduling entity) to UL communication (e.g., transmission by thescheduling entity). UL-centric subframe 700 may also include common ULportion 706. Common UL portion 706 in FIG. 7 may be similar to thecommon UL portion 606 described above with reference to FIG. 6. CommonUL portion 706 may additionally or alternatively include informationpertaining to channel quality indicator (CQI), sounding referencesignals (SRSs), and various other suitable types of information. Theforegoing is merely one example of an UL-centric subframe andalternative structures having similar features may exist withoutnecessarily deviating from the aspects described herein.

In some circumstances, two or more subordinate entities (e.g., UEs) maycommunicate with each other using sidelink signals. Real-worldapplications of such sidelink communications may include public safety,proximity services, UE-to-network relaying, vehicle-to-vehicle (V2V)communications, Internet-of-Everything (IoE) communications, IoTcommunications, mission-critical mesh, and/or various other suitableapplications. Generally, a sidelink signal may refer to a signalcommunicated from one subordinate entity (e.g., UE1) to anothersubordinate entity (e.g., UE2) without relaying that communicationthrough the scheduling entity (e.g., UE or BS), even though thescheduling entity may be utilized for scheduling and/or controlpurposes. In some examples, the sidelink signals may be communicatedusing a licensed spectrum (unlike wireless local area networks (WLAN),which typically use an unlicensed spectrum).

A UE may operate in various radio resource configurations, including aconfiguration associated with transmitting pilots using a dedicated setof resources (e.g., a radio resource control (RRC) dedicated state,etc.) or a configuration associated with transmitting pilots using acommon set of resources (e.g., an RRC common state, etc.). Whenoperating in the RRC dedicated state, the UE may select a dedicated setof resources for transmitting a pilot signal to a network. Whenoperating in the RRC common state, the UE may select a common set ofresources for transmitting a pilot signal to the network. In eithercase, a pilot signal transmitted by the UE may be received by one ormore network access devices, such as an AN, or a DU, or portionsthereof. Each receiving network access device may be configured toreceive and measure pilot signals transmitted on the common set ofresources, and also receive and measure pilot signals transmitted ondedicated sets of resources allocated to the UEs for which the networkaccess device is a member of a monitoring set of network access devicesfor the UE. One or more of the receiving network access devices, or a CUto which receiving network access device(s) transmit the measurements ofthe pilot signals, may use the measurements to identify serving cellsfor the UEs, or to initiate a change of serving cell for one or more ofthe UEs.

Example Error Correction Coding

Many communications systems use error-correcting codes. Specifically,error correcting codes compensate for the intrinsic unreliability ofinformation transfer in these systems by introducing redundancy into thedata stream. Low-density parity-check (LDPC) codes are a particular typeof error correcting codes which use an iterative coding system. Inparticular, Gallager codes are an early example of “regular” LDPC codes.Regular LDPC codes are linear block code in which most of the elementsof its parity check matrix H are ‘0’.

LDPC codes can be represented by bipartite graphs (often referred to as“Tanner graphs”). In a bipartite graph, a set of variable nodescorresponds to bits of a code word (e.g., information bits or systematicbits), and a set of check nodes correspond to a set of parity-checkconstraints that define the code. Edges in the graph connect variablenodes to check nodes. Thus, the nodes of the graph are separated intotwo distinctive sets and with edges connecting nodes of two differenttypes, variable and check.

A lifted graph is created by copying a bipartite base graph (G), whichmay also be known as a protograph, a number of times, Z (referred toherein as the lifting, lifting size, or lifting size value). A variablenode and a check node are considered “neighbors” if they are connectedby an “edge” (i.e., the line connecting the variable node and the checknode) in the graph. In addition, for each edge (e) of the bipartite basegraph (G), a permutation (generally an integer value associated with theedge permutation is represented by k and referred to as the liftingvalue) is applied to the Z copies of edge (e) to interconnect the Zcopies of G. A bit sequence having a one-to-one association with thevariable node sequence is a valid code word if and only if, for eachcheck node, the bits associated with all neighboring variable nodes sumto zero modulo two (i.e., they include an even number of 1's). Theresulting LDPC code may be quasi-cyclic (QC) if the permutations(lifting values) used are cyclic.

FIGS. 8-8A show graphical and matrix representations, respectively, ofan example LDPC code, in accordance with certain aspects of the presentdisclosure. For example, FIG. 8 shows a bipartite graph 800 representingthe LDPC code. Bipartite graph 800 includes a set of five variable nodes810 (represented by circles) connected to four check nodes 820(represented by squares). Edges in bipartite graph 800 connect variablenodes 810 to check nodes 820 (the edges are represented by the linesconnecting variable nodes 810 to check nodes 820). Bipartite graph 800consists of |V|=5 variable nodes and |C|=4 check nodes, connected by|E|=12 edges.

Bipartite graph 800 may be represented by a simplified adjacency matrix,which may also be known as a parity check matrix (PCM). FIG. 8A shows amatrix representation 800A of bipartite graph 800. Matrix representation800A includes a parity check matrix H and a code word vector x, wherex1-x5 represent bits of the code word x. H is used for determiningwhether a received signal was normally decoded. H has C rowscorresponding to j check nodes and V columns corresponding to i variablenodes (i.e., a demodulated symbol), where the rows represent theequations and the columns represents the bits of the code word. In FIG.8A, matrix H has 4 rows and 5 columns corresponding to 4 check nodes and5 variable nodes respectively. If a j-th check node is connected to ani-th variable node by an edge (i.e., the two nodes are neighbors), thenthere is a “1” in the i-th column and in the j-th row of the paritycheck matrix H. That is, the intersection of an i-th row and a j-thcolumn contains a “1” where an edge joins the corresponding vertices anda “0” where there is no edge. The code word vector x represents a validcode word if and only if Hx=0, for example, if for each constraint node,the bits neighboring the constraint (via their association with variablenodes) sum to zero modulo two (0 mod 2)—i.e., they comprise an evennumber of “1s”. Thus, if the code word is received correctly, then Hx=0(mod 2). When the product of a coded received signal and the PCM Hbecomes “0”, this signifies that no error has occurred.

The number of demodulated symbols or variable nodes is the LDPC codelength. The number of non-zero elements in a row (column) is defined asthe row (column) weight d(c)d(v).

The degree of a node refers to the number of edges connected to thatnode.

This feature is illustrated in the matrix H shown in FIG. 8A where thenumber of edges incident to a variable node 810 is equal to the numberof “1s” in the corresponding column and is called the variable nodedegree d(v). Similarly, the number of edges connected with a check node820 is equal to the number of ones in a corresponding row and is calledthe check node degree d(c).

A regular graph or code is one for which all variable nodes have thesame degree, j, and all constraint nodes have the same degree, k. On theother hand, an irregular code has constraint nodes and/or variable nodesof differing degrees. For example, some variable nodes may be of degree4, others of degree 3 and still others of degree 2.

“Lifting” enables LDPC codes to be implemented using parallel encodingand/or decoding implementations while also reducing the complexitytypically associated with large LDPC codes. Lifting helps enableefficient parallelization of LDPC decoders while still having arelatively compact description. More specifically, lifting is atechnique for generating a relatively large LDPC code from multiplecopies of a smaller base code. For example, a lifted LDPC code may begenerated by producing Z number of parallel copies of a base graph(e.g., protograph) and then interconnecting the parallel copies throughpermutations of edge bundles of each copy of the base graph. The basegraph defines the (macro) structure of the code and consists of a number(K) of information bit columns and a number (N) of code bit columns.Lifting the base graph a number of liftings Z results in a final blocklength of KZ. Thus, a larger graph can be obtained by a “copy andpermute” operation where multiple copies of the base graph are made andconnected to form a single lifted graph. For the multiple copies, likeedges that are a set of copies of a single base edge, are permutated andconnected to form a connected graph Z times larger than the base graph.

FIG. 9 is a bipartite graph 900 illustrating the liftings of threecopies of the bipartite graph 800 of FIG. 8. Three copies may beinterconnected by permuting like edges among the copies. If thepermutations are restricted to cyclic permutations, then the resultingbipartite graph 900 corresponds to a quasi-cyclic LDPC with lifting Z=3.The original graph from which three copies were made is referred toherein as the base graph. To obtain graphs of different sizes, a “copyand permute” operation can be applied to the base graph.

A corresponding parity check matrix of the lifted graph can beconstructed from the parity check matrix of the base graph by replacingeach entry in the base parity check matrix with a Z×Z matrix. The “0”entries (those having no base edges) are replaced with the 0 matrix andthe 1 entries (indicating a base edge) are replaced with a Z×Zpermutation matrix. In the case of cyclic liftings the permutations arecyclic permutations.

A cyclically lifted LDPC code can also be interpreted as a code over thering of binary polynomials modulo x^(z)+1. In this interpretation, abinary polynomial, (x)=b₀+b₁x+b₂x²+ . . . +b_(z−1)x^(z−1) may beassociated to each variable node in the base graph. The binary vector(b₀, b₁, b₂, . . . , b_(z−1)) corresponds to the bits associated to Zcorresponding variable nodes in the lifted graph, that is, Z copies of asingle base variable node. A cyclic permutation by k (referred to as alifting value associated to the edges in the graph) of the binary vectoris achieved by multiplying the corresponding binary polynomial by x^(k)where multiplication is taken modulo x^(z)+1. A degree d parity check inthe base graph can be interpreted as a linear constraint on theneighboring binary polynomials B₁(x), . . . , B_(d)(x), written as x^(k)¹ B₁(x)+x^(k) ² B₂(x)+ . . . +x^(k) ^(d) B_(d)(x)=0x^(k) ¹ B₁(x)+x^(k) ²B₂(x)+ . . . +x^(k) ^(d) B_(d)(x)=0, the values, k₁, . . . , k_(d) arethe cyclic lifting values associated to the corresponding edges.

This resulting equation is equivalent to the Z parity checks in thecyclically lifted Tanner graph corresponding to the single associatedparity check in the base graph. Thus, the parity check matrix for thelifted graph can be expressed using the matrix for the base graph inwhich 1 entries are replaced with monomials of the form x^(k) and 0entries are lifted as 0, but now the 0 is interpreted as the 0 binarypolynomial modulo x^(z)+1. Such a matrix may be written by giving thevalue k in place of x^(k). In this case the 0 polynomial is sometimesrepresented as “−1” and sometimes as another character in order todistinguish it from x⁰.

Typically, a square submatrix of the parity check matrix represents theparity bits of the code. The complementary columns correspond toinformation bits that, at the time of encoding, are set equal to theinformation bits to be encoded. The encoding may be achieved by solvingfor the variables in the aforementioned square submatrix in order tosatisfy the parity check equations. The parity check matrix H may bepartitioned into two parts M and N where M is the square portion. Thus,encoding reduces to solving M_(c)=s=Nd where c and d comprise x. In thecase of quasi-cyclic codes, or cyclically lifted codes, the abovealgebra can be interpreted as being over the ring of binary polynomialsmodulo x^(z)+1. In the case of the 802.11 LDPC codes, which arequasi-cyclic, the encoding submatrix M has an integer representation asshown in FIG. 10.

A received LDPC code word can be decoded to produce a reconstructedversion of the original code word. In the absence of errors, or in thecase of correctable errors, decoding can be used to recover the originaldata unit that was encoded. Redundant bits may be used by decoders todetect and correct bit errors. LDPC decoder(s) generally operate byiteratively performing local calculations and passing those results byexchanging messages within the bipartite graph 800, along the edges, andupdating these messages by performing computations at the nodes based onthe incoming messages. These steps may typically be repeated severaltimes and may be referred to as message passing steps. For example, eachvariable node 810 in the graph 800 may initially be provided with a“soft bit” (e.g., representing the received bit of the code word) thatindicates an estimate of the associated bit's value as determined byobservations from the communications channel. Using these soft bits theLDPC decoders may update messages by iteratively reading them, or someportion thereof, from memory and writing an updated message, or someportion thereof, back to, memory. The update operations are typicallybased on the parity check constraints of the corresponding LDPC code. Inimplementations for lifted LDPC codes, messages on like edges are oftenprocessed in parallel.

LDPC codes designed for high speed applications often use quasi-cyclicconstructions with large lifting factors and relatively small basegraphs to support high parallelism in encoding and decoding operations.LDPC codes with higher code rates (e.g., the ratio of the message lengthto the code word length) tend to have relatively fewer parity checks. Ifthe number of base parity checks is smaller than the degree of avariable node (e.g., the number of edges connected to a variable node),then, in the base graph, that variable node is connected to at least oneof the base parity checks by two or more edges (e.g., the variable nodemay have a “double edge”). If the number of base parity checks issmaller than the degree of a variable node (e.g., the number of edgesconnected to a variable node), then, in the base graph, that variablenode is connected to at least one of the base parity checks by two ormore edges. Having a base variable node and a base check node connectedby two or more edges is generally undesirable for parallel hardwareimplementation purposes. For example, such double edges may result inmultiple concurrent read and write operations to the same memorylocations, which in turn may create data coherency problems. A doubleedge in a base LDPC code may trigger parallel reading of the same softbit value memory location twice during a single parallel parity checkupdate. Thus, additional circuitry is typically needed to combine thesoft bit values that are written back to memory, so as to properlyincorporate both updates. Eliminating double edges in the LDPC codehelps to avoid this extra complexity

LDPC code designs based on cyclic lifting can be interpreted as codesover the ring of polynomials modulo may be binary polynomials modulox^(z)+1, where Z is the lifting size (e.g., the size of the cycle in thequasi-cyclic code). Thus encoding such codes can often be interpreted asan algebraic operation in this ring.

In the definition of standard irregular LDPC code ensembles (degreedistributions) all edges in the Tanner graph representation may bestatistically interchangeable. In other words, there exists a singlestatistical equivalence class of edges. A more detailed discussion oflifted LDPC codes may be found, for example, in the book titled, “ModernCoding Theory,” published Mar. 17, 2008, by Tom Richardson and RuedigerUrbanke. For multi-edge LDPC codes, multiple equivalence classes ofedges may be possible. While in the standard irregular LDPC ensembledefinition, nodes in the graph (both variable and constraint) arespecified by their degree, i.e., the number of edges they are connectedto, in the multi-edge type setting an edge degree is a vector; itspecifies the number of edges connected to the node from each edgeequivalence class (type) independently. A multi-edge type ensemble iscomprised of a finite number of edge types. The degree type of aconstraint node is a vector of (non-negative) integers; the i-th entryof this vector records the number of sockets of the i-th type connectedto such a node. This vector may be referred to as an edge degree. Thedegree type of a variable node has two parts although it can be viewedas a vector of (non-negative) integers. The first part relates to thereceived distribution and will be termed the received degree and thesecond part specifies the edge degree. The edge degree plays the samerole as for constraint nodes. Edges are typed as they pair sockets ofthe same type. The constraint that sockets must pair with sockets oflike type characterizes the multi-edge type concept. In a multi-edgetype description, different node types can have different receiveddistributions (e.g., the associated bits may go through differentchannels).

Puncturing is the act of removing bits from a code word to yield ashorter code word. Thus, punctured variable nodes correspond to codeword bits that are not actually transmitted. Puncturing a variable nodein an LDPC code creates a shortened code (e.g. due to the removal of abit), while also effectively removing a check node. Specifically, for amatrix representation of an LDPC code, including bits to be punctured,where the variable node to be punctured has a degree of one (such arepresentation may be possible through row combining provided the codeis proper), puncturing the variable node removes the associated bit fromthe code and effectively removes its single neighboring check node fromthe graph. As a result, the number of check nodes in the graph isreduced by one.

FIG. 11 is a simplified block diagram illustrating am encoder, inaccordance with certain aspects of the present disclosure. FIG. 11 is asimplified block diagram 1100 illustrating a portion of radio frequency(RF) modem 1150 that may be configured to provide a signal including anencoded message for wireless transmission. In one example, convolutionalencoder 1102 in a BS 110 (or a UE 120 on the reverse path) receivesmessage 1120 for transmission. Message 1120 may contain data and/orencoded voice or other content directed to the receiving device. Encoder1102 encodes the message using a suitable modulation and coding scheme(MCS), typically selected based on a configuration defined by the BS 110or another network entity. Encoded bit stream 1122 produced by encoder1102 may then be selectively punctured by puncturing module 1104, whichmay be a separate device or component, or which may be integrated withencoder 1102. Puncturing module 1104 may determine that the bit streamshould be punctured prior to transmission or transmitted withoutpuncturing. The decision to puncture bit stream 1122 may be made basedon network conditions, network configuration, RAN defined preferences,and/or for other reasons. Bit stream 1122 may be punctured according topuncturing pattern 1112 and used to encode message 1120. Puncturingpattern 1112 may be based on LDPC code designs as described in moredetail below. Puncturing module 1104 provides output 1124 to mapper 1106that generates a sequence of Tx symbols 1126 that are modulated,amplified and otherwise processed by Tx chain 1108 to produce RF signal1128 for transmission through antenna 1110.

Output 1124 of puncturing module 1104 may be the unpunctured bit stream1122 or a punctured version of bit stream 1122, according to whethermodem portion 1150 is configured to puncture bit stream 1122. In oneexample, parity and/or other error correction bits may be punctured inoutput 1124 of encoder 1102 in order to transmit message 1120 within alimited bandwidth of the RF channel. In another example, bit stream 1122may be punctured to reduce the power needed to transmit message 1120, toavoid interference, or for other network-related reasons. Thesepunctured code word bits are not transmitted.

The decoders and decoding algorithms used to decode LDPC code wordsoperate by exchanging messages within the graph along the edges andupdating these messages by performing computations at the nodes based onthe incoming messages. Each variable node in the graph is initiallyprovided with a soft bit, termed a received value, that indicates anestimate of the associated bit's value as determined by observationsfrom, for example, the communications channel. Ideally, the estimatesfor separate bits are statistically independent. This ideal may beviolated in practice. A received word is comprised of a collection ofreceived values.

FIG. 12 is a simplified block diagram illustrating a decoder, inaccordance with certain aspects of the present disclosure. FIG. 12 is asimplified schematic 1200 illustrating a portion of RF modem 1250 thatmay be configured to receive and decode a wirelessly transmitted signalincluding a punctured encoded message. The punctured code word bits maybe treated as erased. For example, the LLRs of the punctured nodes maybe set to “0” at initialization. De-puncturing may also includedeshortening of shortened bits. These shortened bits are not included ina transmission and, at the receiver, shortened bits are treated as knownbits, typically set to “0”, allowing LLR magnitude to be set to themaximum possible. In various examples, modem 1250 receiving the signalmay reside at the access terminal (e.g., UE 120), at the base station(e.g., BS 110), or at any other suitable apparatus or means for carryingout the described functions. Antenna 1202 provides an RF signal 1220 tothe receiver. RF chain 1204 processes and demodulates RF signal 1220 andmay provide a sequence of symbols 1222 to demapper 1206, which producesbit stream 1224 representative of the encoded message (e.g., message1120).

Demapper 1206 may provide a depunctured bit stream 1224. In one example,demapper 1206 may include a depuncturing module that can be configuredto insert null values at locations in the bit stream at which puncturedbits were deleted by the transmitter. The depuncturing module may beused when puncture pattern 1210 used to produce the punctured bit streamat the transmitter is known. Puncture pattern 1210 can be used toidentify LLRs 1228 that may be ignored during decoding of bit stream1224 by convolutional decoder 1208. The LLRs may be associated with aset of depunctured bit locations in bit stream 1224. Accordingly,decoder 1208 may produce decoded message 1226 with reduced processingoverhead by ignoring identified LLRs 828. The LDPC decoder may include aplurality of processing elements to perform the parity check or variablenode operations in parallel. For example, when processing a code wordwith lifting size Z, the LDPC decoder may utilize a number (Z) ofprocessing elements to perform parity check operations on all edges of alifted graph, concurrently.

Processing efficiency of decoder 1208 may be improved by configuring thedecoder 1208 to ignore LLRs 1228 that correspond to punctured bits in amessage transmitted in punctured bit stream 1222. Punctured bit stream1222 may have been punctured according to a puncturing scheme thatdefines certain bits to be removed from an encoded message. In oneexample, certain parity or other error-correction bits may be removed. Apuncturing pattern may be expressed in a puncturing matrix or table thatidentifies the location of bits to be punctured in each message. Apuncturing scheme may be selected to reduce processing overhead used todecode message 1226 while maintaining compliance with data rates on thecommunication channel and/or with transmission power limitations set bythe network. A resultant punctured bit stream typically exhibits theerror-correcting characteristics of a high rate error-correction code,but with less redundancy. Accordingly, puncturing may be effectivelyemployed to reduce processing overhead at decoder 1208 in the receiverwhen channel conditions produce a relatively high signal to noise ratio(SNR).

At the receiver, the same decoder used for decoding non-puncturedbitstreams can typically be used for decoding punctured bitstreams,regardless of how many bits have been punctured. In conventionalreceivers, the LLR information is typically de-punctured before decodingis attempted by filling LLRs for punctured states or positions(de-punctured LLRs) with zeros. The decoder may disregard de-puncturedLLRs that effectively carry no information based in part, on what bitsare punctured. The decoder may treat shortened bits as known bits (e.g.,set to “0”).

Example High Performance, Flexible, and Compact Low-Density Parity-Check(LDPC) Code

Certain aspects of the present disclosure provide low-densityparity-check (LDPC) code designs that offer high-performance and areflexible and compact. As will be described in greater detail below, theLDPC codes may be used for large ranges of code rates, blocklengths, andgranularity, while being capable of fine incremental redundancy hybridautomatic repeat request (IR-HARQ) extension and maintaining good errorfloor performance, a high-level of parallelism for high throughoutperformance, and a low description complexity.

Example Independent Clustering Scheme for Efficiently Lifting LDPC Codes

In a wireless communication system (e.g., wireless communications system100), a set of error correcting codes (e.g., LDPC codes) may be used,for example, for various ranges of blocklengths and/or code rates to beused. To increase efficiency in terms of implementation and compactnessof description, it is desirable that the set of codes are related.

As described above with respect to FIG. 9, a base graph or parity checkmatrix (PCM) (having K information bits-columns and N total transmittedbit-columns) can be copied, and random permutations to each edge bundleto interconnect the copies, to provide a lifted LDPC code. Practicalcodes use cyclic permutations or circulant permutation matrices tointerconnect the copies of the lifted base graph, resulting inquasi-cyclic codes, which may be easier to implement in hardware. In anexample, for a lifting value Z, each edge in the base PCM is associatedwith an integer lifting value k in the range [0, Z−1]. The associatedinteger represents the cyclic shift of the identity matrix by thatinteger. A table may be used for the base PCM showing entries for thebit columns and check nodes. Each entry corresponds to the circulantmatrix that is the identity matrix cyclically shifted by the integervalue associated with an edge between a variable node and a check node.The entry ‘.’ May be used when there is no edge present between a basevariable node and a base check node.

When the base graph is reused without alteration the code rate (given byK/N) is same for all liftings Z (corresponding to the number of liftingsor copies of the base graph). Using different lifting values can providea set of codes (e.g., a code family) to achieve a range of block lengths(given by KZ). Thus, using different lifting values for the unalteredbase graph can achieve a set of codes with a similar code rate but fordifferent block lengths. For different codes rates, different basegraphs may be used.

To generate/describe a set of codes (e.g., code family) for a range ofcode rates and/or block lengths, one way to design the code family is todesign a different base PCM for each code rate and each lift value. Forexample, in 802.11n there are four code rates (1/2, 2/3, 3/4 5/6) andthree blocklengths (648, 1296, 1944) corresponding to the lift values of(27, 54, 81). There is a unique base PCM of size 24 bit-columns for each“tuple” (i.e., each pair of code rate and lift value) resulting intwelve base PCMs (e.g., for the combinations of code rate and liftvalue: (1/2, 27), (1/2, 54), (1/2, 81), . . . (5/6, 81)). Thus, forlarge Z, the set of liftings Z and lifting values k can lead to a largedescription complexity.

Techniques for efficiently describing/generating the set of liftings aredesirable.

A set of liftings for a single parity matrix may be efficientlydescribed as an increasing series of liftings that are closely spaced toeach other in value. This allows liftings to be specified in a narrowrange with a common set of bits, allowing for a compact description andgood performance.

FIG. 13 is a flow diagram illustrating example operations 1300 forencoding and transmitting a code word using a base graph structure,according to aspects of the present disclosure. Operations 1300 may beperformed, for example, by a transmitter/encoder device (e.g., such as aBS 110 or a UE 120). Operations 1300 begin at 1302 by determining a basematrix. The base matrix is associated with a cluster of lifting sizevalues. At 1304, the transmitter device selects a lifting size value, Z,for generating a lifted LDPC codes by permutations of edges in the basematrix. The lifting size values in the cluster of lifting size valuesare within a defined range of each other. At 1306, the transmitterdevice generates a lifted matrix based, at least in part, on the basematrix and the selected lifting size value. At 1308, the transmitterdevice uses the generated lifted matrix to generate the lifted LDPCcode. At 1310, the transmitter device encodes a set of information bitsbased on the lifted LDPC code to produce a code word. At 1312, thetransmitter device transmits the code word over a wireless medium.

According to aspects of the present disclosure, a set liftings Z for asingle base graph or PCM, to obtain a family of LDPC codes can bedescribed (e.g., determined/generated) using lifting values that areclose to each other in value for a compact description.

The family of LDPC codes can be obtained using a base graph togetherwith an increasing series of liftings with lifting values Z₁, Z₂, . . ., Z_(n) which may be referred to herein as a “tower” of liftings. Acluster includes members which are within a defined range of each other.For example, members of a cluster may be within a certain ratio of eachother. In some cases, the values of the members of the cluster may bewithin a ratio of two of each other.

One example of a cluster is the set of lifting values {4, 5, 6, 7}having a maximum ratio of 7/4. A tower can be obtained by applying anexponential power to an integer, such as a power of 2. Thus, a tower ofclustered liftings may consist of the integers 2^(j) {4, 5, 6, 7} forj=1, . . . , 7. This gives an approximately exponentially spaced set of28 values for Z. Put another way, this gives the tower Z₁, Z₂, . . . ,Z₂₈=8 (2¹*4), 10, 12, 14, . . . , 896 (2⁷*7). For a fixed j the fourlifting values are within a factor of 7/4 of each other and may form acluster of lifting values. For j=1, . . . , 7, a tower of clusteredliftings may be represented as 2^(j) {4,5,6,7}. While the presentexample includes a set of lifts within a factor of 2 as clustered, otherfactors, (e.g., 3, 4 . . . , etc.) may be used. These factors need notbe consecutive, but should be numerically within a defined range of eachother.

According to certain aspects, for any lifting size Z in the set ofclustered liftings, the associated integer lifting values k for the edgepermutations may be used for any of the other liftings in the set ofclustered liftings. For example, lifting values may be designed forZ=2^(j)4 that are also good for 2^(j){5, 6, 7}. Thus, describing (e.g.,determining/generating/indicating/storing) a family of LDPC codes may beperformed by identifying sets of clustered lift values (associated toedges in a base graph) that are close to each other, such as within afactor (e.g., a factor 2 or 3) of each other. In the example above, thiscorresponds to identifying the set of lifting values {4, 5, 6, 7} andthe other sets in the tower of liftings, {16, 20, 24, 28}, {32, 40, 48,56}, . . . {512, 640, 768, 896}, which are within a factor of 2 of eachother. For each clustered set of liftings, the base PCM for the smallestlift value in the cluster (e.g., Z=8) may be optimized. That optimizedbase PCM may be used for the other lift values in that cluster (e.g.,Z=10, Z=12, Z=14). Similarly, the optimized base PCM can be determinedfor the other sets of clustered liftings.

Thus, liftings within a defined range of each can be specified (e.g.,stored/indicated) other with a common set of bits. For example, j+2 bitsper lifting value may be used to specify all lifts for the four statedliftings in the cluster 2^(j) {4,5,6,7}.

These liftings may be further improved by having additional bits. Forexample, using j+3 bit to represent the lifting values k on an edge anddefining the lifting by taking the j+3 bit value modulo Z for Z in 2^(j){4, 5 ,6, 7} results in a lifting for Z=2^(j)*4 given by the j+2 lowerorder bits and the higher order bit affects only the other 3 liftings.Higher order bits can similarly be used. The example presents a range ofliftings within a factor of 2 of each other and all are specified usinga j+2 (or slightly larger) bits. However, other factors may be used, solong as the factors are numerically within a defined range of eachother.

Generally, optimization of lifts and graphs targets reducing the numberof small loops in the Tanner graph of the LDPC code. A loop in thelifted Tanner graph corresponds with a loop in the base graph byprojecting the loop onto the base graph. Additional optimizations maytake into account the degrees of nodes in the loops In the case ofmatched lifted graphs (e.g., cyclically lifted graphs) a loop in thebase graph is also a loop in the lifted Tanner graph precisely when thelifting values traversed in the loop reduce to the identity permutation.

According to certain aspects, using j+3 bit to represent the lifting anddefining the lifting by taking the j+3 bit value modulo Z for Z in 2^(j){4,5,6,7} results in a lifting for Z=2^(j) 4 given by the j+2 lowerorder bits and the higher order bit affects only the other 3 liftings.

For the optimization of the base graph for a set of clustered liftings,liftings values may be selected within a range [0,(2^(j)*4)−1]. In otherwords, the lifting values may be selected from a range that is smallerthan the smallest lifting size in the set of clustered liftings. Thus,in example described herein, for the tower of clustered liftings forj=1, the lifting size values may be selected from the range [0:7].

For cyclically lifted graphs, each edge in the base graph has anassociated integer as a lifting value. The value is taken positivelywhen the edge is traversed in the variable-to-check direction andnegatively in the check-to-variable direction. Given a loop in the basegraph and a lifting size Z, the base loop will also be a lifted loop ifthe loop sum of the corresponding integers is 0 or has Z as a factor.Thus, when choosing integer value in the range [0,2^(j)4] for thelifting values, the goal for Z=2^(j)4 is to avoid summing to 0 or tohaving a factor of 2^(j)4 in the loop sum. For small loops, the sumgenerally will not be large, so in general, there are more such loopswith a sum of magnitude 2^(j)4 than those with a sum of magnitude2*2^(j)4 or 3*2^(j)4. Similarly, on average, sums of magnitude 2^(j){5,6, 7} and its multiples are less frequent. Thus, the small loopavoidance design problem is similar for these closely related values,where lift values in the range [0:2^(j) 4] uses more than half the rangeavailable for Z=2^(j){5, 6, 7}. For a much larger Z, the used portionwould be smaller and there may be a bigger gap between the bestperformance available for the large Z and that achievable by restrictingliftings to a smaller Z. Thus, applying this approach over a relativelysmall range of Z values (e.g., within a factor of 2) is prudent. Hence,it is possible to find lift values that give good performance for fourvalues simultaneously.

By utilizing a range of liftings which are numerically within a definedrange along with an independent set of bits for each j with j=1, . . . ,7 the number of bits required is 3+4+5+6+7+8+9=42 bits per edge tospecify all of the liftings. By creating dependencies between differentvalues of j this requirement may be further reduced. Additionally, oftena structured LDPC graph will have special edges whose lifting values maybe determined directly. For example, the edges connecting degree onevariable nodes may always have lifting value 0. Edges on accumulatechains in encoding structures are also often set to 0. Such fixedlifting structure may not vary as the liftings vary and may be referredto as having a special invariant structure. The lifting values for suchedges can be more compactly represented. However, the number of edgeshaving such a special invariant structure is a small portion of thetotal number of edges in the graph and does not significantly detractfrom the benefits of the above method for those edges that do not have aspecial invariant structure.

Example Nested Scheme for Efficiently Lifting LDPC Codes

As described above, liftings in a clustered set of liftings (e.g., a“tower” of liftings”) can use the same lifting values (integersassociated with the edge permutations) and, thus, the number of bitsused to specify all of the liftings and lifting values may be reduced.This size reduction may allow for a reduced amount of memory for storingdescriptions of all of the LDPC codes.

According to aspects of the present disclosure, a nested scheme forefficiently lifting LPDC codes may be used that further reduces thenumber of bits per edge in the base PCM.

As all liftings, even for different j values (e.g., liftings indifferent clustered sets), are based on the same base graph, thestructures found to work for a small j value (i.e., for liftings in thecorresponding set of clustered liftings) may be scaled and reused forlarger j values (i.e., for larger liftings in another set). For example,a structure optimized for a smaller j may be retained and scaled for alarger j in order to reuse optimized bits found for the smaller j.

FIG. 14 is a flow diagram illustrating example operations 1400 forencoding and transmitting a code word using a base graph structure,according to aspects of the present disclosure. Operations 1400 may beperformed, for example, by a transmitter/encoder device (e.g., such as aBS 110 or a UE 120). Operations 1400 begin at 1402 by determining a basematrix. The base matrix is associated with a cluster of lifting sizevalues. At 1404, the transmitting device selects a first lifting sizevalue from the cluster of lifting size values for generating a liftedlow density parity check (LDPC) codes by permutations of edges in thebase matrix. The lifting size values in the cluster of lifting sizevalues are within a defined range of each other. At 1406, thetransmitting device generates a first lifted matrix based, at least inpart, on the base matrix and selected first lifting size value. At 1408,the transmitting device selects a set of bits associated with theselected first lifting size value. At 1410, the transmitting deviceselects a second lifting size value from the cluster of lifting sizevalues. At 1412, the transmitting device generates a second liftedmatrix, based, at least in part, on the base matrix, second selectedlifting size value, and the set of bits. At 1414, the transmittingdevice uses the generated second lifted matrix to generate the liftedLDPC code. At 1416, the transmitting device encodes a set of informationbits based on the lifted LDPC code to produce a code word. At 1418, thetransmitting device transmits the code word. In the example describedabove, for j=1, the set of clustered liftings is Z={8, 10, 12, 14} maybe designed using lifting values in the range [0, 1, 2, . . . 7].According to certain aspects, the liftings values selected for the j=1graph can be multiplied by 2 and used for the j=2 graph, where the setof clustered liftings is Z={16, 20 ,24, 28}. In this case, the largerlifted graph (for j=2) inherits and improves on the loop structure ofthe smaller graph as the larger graph for lifting 2Z consists of twoparallel copies of the original smaller graph with lifting Z. Becausethe smaller graph is designed to avoid loops summing to a factor of Z,it also avoids loops summing to factors of 2Z. j=1 and j=2 are merelyexemplary. In aspects, the lifting values for any set of clusteredliftings may be used for another set of larger clustered liftings, andthe lifting values can be multiplied by the factor of the difference inthe liftings sizes of the two sets of liftings.

Further optimization of the larger graph could be achieved by alteringthe lowest order bit in the liftings. For example, after multiplicationby 2 all liftings would have their lowest order bit set to 0. Moregenerally, to achieve the best possible performance, more than just thelowest order bit may be altered. For example, two or three leastsignificant bits may be altered. Generally, optimizing the three leastsignificant bits results in nearly optimal performance. This preservesthe large scale properties of the liftings (the most significant) bits,scaled up accordingly (by multiplying by 2) and then refines the details(the lower order bits) to find an optimal solution for the base graphfor the next set of clustered liftings.

In one example, the three lowest order bits may be re-optimized. For theset of clustered liftings j=1, a 3-bit optimized lift per edge may beobtained. If the lifting values for an edge in the base graph (e.g., forthe smallest lifting in the set j=1) are a, y, and z (i.e., 3 bits) inbase 2 (i.e., where each of a, y, and z is an integer values of 0 or 1),then for the base graph for the set of clustered liftings j=2, the sameedge will have lifting values of a, b, w, x, (i.e., 4 bits with one bitcopied from the j=1 family) and in the base graph for the set ofclustered liftings j=3, the edge will have lifting values a, b, c, u, v,(5 bits with 2 bits copied from the j=2 family) etc. Thus, the basegraph for the set of clustered liftings j=7, the edge will have liftingvalue a, b, c, d, e, f, g, r, s (i.e., 9 bits with 7 bits copied fromthe j=6 family) and the bits a, b, c, d, e, f, g are reused for smallerset of clustered liftings j while the bits r and s are unique to j=7.The base graph for the set of clustered liftings uses j common bits and2 unique bits. Thus, for all of the families j=1 . . . 7, there is atotal of seven common bits and fourteen unique bits (i.e., 2 unique bitsfor each j), for a total of 21 bits to describe all seven code families.This is referred to as a “nested” scheme for describing the families ofLDPC codes. If only the two lowest order bits were re-optimized thenonly 14 bits total would be needed. In some examples, most significantbits (MSBs) or any subset of consecutive bits can be used as commonbits, rather than the LSBs. Both cases offer a substantial improvementon the 42-bit independent case.

As discussed above, certain structured LDPC graph may have a specialinvariant structure, for example, some special edges may have liftingsthat are invariant. For example, the 802.11 encoding structure, usesliftings of values 0 and 1. If this structure is retained, the structureis consistent with the above optimization of lower order bits only whenat least two of the lower order bits are optimized. This is because2×1=2; so if only the lowest order bit is optimized, the value 1 cannotbe reached as only 2 and 3 are possible values. In this case it may bepreferable to retain the lifting value of 1. A similar technique can beused in which the low order bits are retained across different j and thehigher order bits are re-optimized. In general, some bits from a smallerj may be reused to define values for the larger j while leaving enoughbits for optimization so as to achieve good performance.

Example Compactly Described Family of LDPC Codes

As described above, large collections of lifting values and liftings forsets of clustered LDPC codes may be compactly described (e.g.,represented/generated/determined/stored). For a given base graph, thisprovides a compact way of obtaining a large range of blocklengths.However, it may be desirable to also support many different code rates,which may require many different base graphs. In addition, thegranularity of the block lengths is exponential. In practice, finergranularity in blocklength may be desirable. Finer granularity can beachieved through puncturing and shortening, thus proper code designaccounting for the puncturing and/or shortening may be desirable toensure high performance of the coding system. LDPC codes can be designedwith HARQ extensions (e.g., IR-HARQ extensions). Thus, the base graphstructure may support a range of code rates from a highest rate, whichmay be used for a first transmission in a HARQ sequence, down to somelowest supported rate.

Aspects of the present disclosure provide a base graph structure tocombine with a set of liftings Z (for example, with a set clusteredlifting values or a family of liftings), for a single-bit granularity inblocklength over a wide range of block sizes.

FIG. 15 is a flow diagram illustrating example operations 1500 forencoding and transmitting a codeword using a base graph structure,according to aspects of the present disclosure. Operations may beperformed by a wireless device, for example, the a transmitting device(e.g., a BS 110 or a UE 120). Operations 1500 begin at 1502 withobtaining K information bits and a desired code-block length N. At 1504,the wireless device selects a lifting size Z, from a tower of liftingsizes associated with a set of base graphs. At least one base graph ofthe set of base graphs has a minimum number, k_(b,min), of informationbit-columns and a maximum number, k_(b,max), of information bit-columnsand Z, is selected such that k_(b,min) is less than or equal to K/Z_(i)and K/Z_(i) is less than or equal to k_(b,max). At 1506, the wirelessdevice selects a base graph from the set of base graphs, the selectedbase graph having k_(b) information bit-columns. k_(b) is equal to asmallest integer greater than or equal to K/Z_(i). At 1508, the wirelessdevice generates N-K parity bits based on the K information bits andencoding the K information bits and the N-K parity bits using theselected base graph to generate a code word. At 1510, the wirelessdevice transmits the code word via a wireless medium.

FIG. 16 shows a structure of an example base PCM 1600, in accordancewith certain aspects of the present disclosure. As shown in FIG. 16, theexample base PCM 1600 has information (systematic) bit columns 1602(i.e., variable nodes) which include a “core” structure 1606 of somenumber of degree 3 or higher variable nodes along with some state(punctured) nodes 1602 that are of higher degree, which together formthe set of information bit columns 1602. For simplicity of description,all of the systematic bit columns other than the high degree puncturedstate nodes are degree 3, but the disclosed techniques are not solimited.

As shown in FIG. 16, the base PCM 1600 structure includes a paritystructure 1610. The parity structure 1610 includes an accumulate chainterminated by a degree 3 node (e.g., similar to the IEEE 802.11nstandard LDPC code). Alternate encoding structures may be used, forexample to support deeper error floors, and the disclosed techniques maybe applied to such variations on the encoding structure. As shown inFIG. 16, the base PCM 1600 structure may also include one or more degreeone parity bits 1608. The degree one parity bits 1608 are connected viaa check node only to the state nodes.

The bit columns 1602 and parity structure 1610 may be referred to as the“core graph” or “core PCM”. As shown in FIG. 16, the core graph can beextended using additional parity-bits further IR-HARQ transmissions(IR-HARQ extensions 1612) to define codes of a lower code rate than therate associated to the core graph. The complete graph or some portionbeyond the core graph may be referred to as an “extended graph”. Thecore graph has an associated code rate determined by its parameters(i.e., variable nodes, check nodes, edges, puncturing, etc.). Someparity bits in the core graph can be punctured to support code ratesabove the code rate of the core graph. Lower coding rates may beobtained by extending the core graph with parity bits.

Aspects of the present disclosure focus on the degree three corevariable nodes, but the aspects may be applied even if some of thevariable nodes involved have a different core degree. The core degreecould be higher than three, for example. A base graph design may becombined with a suitable set of lifting values to achieve finegranularity in blocklength (single-bit granularity).

According to certain aspects, shortening of the base graph and thelifted graph may be used to achieve the finer granularity inblocklength. The core graph may have a maximum number of informationcolumns, denoted by k_(b,max). When the base code is shortened, one ormore information bits are declared known (e.g., by setting the bit to 0}and they are not used in the transmitted code. When a bit in the basegraph is known, the entire corresponding column of Z bits in the liftedgraph is declared known. The receiver may know a priori the bits thatare fixed to 0 and can exploit that knowledge in the decoding process.In parallel decoding architectures an entire known column can be skippedin the decoding process, so the known column incurs no operations at thereceiver, hence the coding system can operate as if the base graph wereactually smaller. This does not typically apply to shortening that isless than an entire column.

According to aspects of the present disclosure, a base graph structurethat gives very good performance for shortening over some range isprovided. The shortening of the base graph results in a range ofsupported information columns from a minimum value of k_(b,min) up to amaximum value of k_(b,max). The structure of the shortening guaranteesthat at most one lifted column of information bits of the lifted graphwill be partially shortened. All other information bit columns may becompletely used or completely shortened (e.g., shortened at the basegraph level).

According to aspects of the present disclosure, a base graph structureis provided which, when combined with carefully chosen lift values,provides a compact coding solution and allows transmissions usingarbitrary rates and blocklengths with good performance.

The tower of liftings is a discrete set {Z₁, Z₂, . . . , Z_(m)} where Z₁denotes the minimum lifting size and Z_(m) denotes the maximum liftingsize. According to certain aspects, k_(b,min) and k_(b,max) may beselected such that the ratio k_(b,max)/k_(b,min) is at least as large asthe maximum value of Z _(i+1) /Z_(i) for all values of i. This mayprovide the basis for fine granularity in information blocklength.

In addition to the information bits in the base graph, the base graphstructure can support a number or parity bits in the range from aminimum of c_(b,min) to a maximum of c_(b,max). The minimum may be lessthan the number of parity bits in the core graph (e.g., some parity bitsmay be punctured) to support higher transmission rates. The maximumnumber of parity bits c_(b,max) corresponds to the maximum number of theparity bits in the extended graph and may be substantially larger thanthe number of parity bits in the core graph.

According to aspects of the present disclosure, the base graph can bedesigned by a process of successive optimization to ensure that the basegraphs for all supported shortenings yield good performance. Anexemplary technique for designing an optimized base graph 1700 isdiscussed with respect to FIG. 17. To obtain the optimized base graph1700, a base graph with k_(b,min) information bit columns 1706 (for boththe core and the extended base graph), including the state nodes 1702and core 1704, may be optimized. The total number of parity bits isequal to c_(b,max)−c_(b,min) and may be obtained by puncturing degreetwo parity bit columns in the core graph so that the base graph yieldsthe desired highest possible coding rate. Once the base graph withk_(b,min) information bit columns is obtained, a column 1710 to optimizethe base graph for performance over k_(b,min)+1 information bit columns.Adding of bit columns 1710 to the base graph is repeated in an iterativeprocess until an optimized base graph on k_(b,max) information bitcolumns 1708 is obtained.

The maximum rate and the minimum rate that can support all blocklengthsin the range of blocklength (k_(b,min) to k_(b,max)) are given byr_(max)=k_(b,min)/(k_(b,min)−p_(b)+c_(b,min)) andr_(min)=k_(b,max)/(k_(b,max)−p_(b)+c_(b,max)), where p_(b) denotes thenumber of punctured information columns. In general, c_(b,min) can beless than the number of parity bits in the core, because the design cansupport puncturing of core parity bits. c_(b,core) can be used to denotethe number of parity bits in the core. The code rate of the core can begiven by r_(core)=k_(b,min)/(k_(b,min)−p_(b)+c_(b,core)) as the highestrate which can be supported by all k_(b,min)≦k_(b)≦k_(b,max) withoutpuncturing core bits. In principle, one can always take k_(b,min) to bevery small, but then the performance of the code at the highest rater_(max) might degrade. k_(b,min) should be large enough to providedesirable performance at the highest rate.

The technique of nested base graph construction described above ensuresthat for any k_(b,min)·Z₁≦K≦k_(b,max)·Z_(m) and any N such thatr_(min)≦K/N≦r_(max), a code from the base graph that has a desirableperformance can be obtained. For any pair of lifts Z_(i) and Z_(i+1),k_(b,min)·Z_(i+1)≦k_(b,max)·Z_(i) by construction. Thus, as long as thedesired information blocklength size K is in the range,k_(b,min)·Z_(i)≦K≦k_(b,max)·Z_(m), then there exists a k_(b) ink_(b,min)≦k_(b)≦k_(b,max) and a Z_(i) in Z₁≦Z_(i)≦Z_(m) such thatk_(b)·Z_(j)≦K≦(k_(b)+1)·Z_(i). Thus, a desired information blocklength Kmay be obtained by using the base graph with k_(b) information bitcolumns followed by shortening of at most Z_(i) information bits. Theparity bits may then be obtained by puncturing of at most Z_(i)parity-bits from the end. An exception to this might occur in the casewhere the number of base parity bits is fewer than the number of basecore parity bits. In this case is may be desirable to keep all coreparity bits in the description of the code and puncture as needed toachieve the desired code rate. Since the base graph was constructedusing the nested procedure described above, the shortening andpuncturing by at most Z_(i) may still have desirable performance.

The above optimized base graph structure, which can support rates in therange [r_(min), r_(max)] and blocklengths in the rangek_(b,min)·Z₁≦K≦k_(b,max)·Z_(m), may be referred to as a family.Typically, the set of lifts in the family is a tower of clusteredliftings, as previously described.

Thus, to construct a code of a desired blocklength N (K informationbits), the Z_(i) can be selected that satisfiesk_(b,min)≦K/Z_(i)≦k_(b,max), which is always possible becauseγ≧k_(b,max)/k_(b,min). The base graph can be set to k_(b)=K/Z_(i). Ingeneral, k_(b)·Z₁≦K≦(k_(b)+1)Z_(i), so at most one column may beshortened. Parity bits N-K in the range[c_(b,min)·Z_(i):c_(b,max)·Z_(i)] can be added to the base graph.

In an example, a base graph may have information bit columns with[k_(b,min):k_(b,max)]=[24:30] with two punctured bits, p_(b)=2, andparity bit columns for each k_(b) with [c_(b,min):c_(b,max)][5:152] andc_(b,core)=7. The core 1800 of the PCM for this example base graph isillustrated in FIG. 18.

FIG. 18 is a table illustrating degree three checks and puncturing for ahigh rate code, in accordance with certain aspects of the presentdisclosure. FIG. 18A is a table illustrating the core part of the PCMfor the optimized base graph of FIG. 17, used to get the tableillustrated in FIG. 18, in accordance with certain aspects of thepresent disclosure.

The maximum rate and the minimum rate for which all blocklengths inrange are supported is r_(max)=8/9=24/27 (if two additional core paritybits are punctured) and r_(min)=1/6. For lifting sizes (e.g., a set ofclustered liftings as described in the sections above) given by Z=2^(j){4,5,6,7} with 2≦j≦7, Z₁, Z₂, . . . , Z_(max)=8, 10, 12, 14, 16, 20, 24,28, 32, . . . , 512, 640, 768, 896. If one definesγ=max_(i)[Z_(i+1)/Z_(i)]=5/4, then it follows thatk_(b,max)/k_(b,min)≧γ. Therefore, this family of base graphs cangenerate codes that support all (K, N) where 192≦K≦26,880 and1/6≦K/N≦8/9. Thus, one family of codes that supports all rates from 8/9to 1/6 and all blocklengths from a minimum of 192 to a maximum of 26,880with desirable performance for any rate and blocklength pair isprovided.

Example Compactly Described Family of LDPC Codes Using Regular CheckDegrees

Techniques for compactly representing large collections of liftings inlifted LDPC codes and shortening of base graphs with a set of liftingvalues to provide fine granularity in blocklength are described above.

Techniques are provided herein for designing the base graphs forperformance across the shortened sequence. Aspects of the presentdisclosure describe properties and structure for the base graph of afamily that provides for high performance in base graphs that useshortening. For example, aspects of the present disclosure describesexamples of how the shortened information nodes may be connected in thebase graph.

Density evolution analysis (which reveals asymptotic performance of anLDPC structure) indicates that desirable performance can be achievedwhen the submatrix of the degree 3 portion of the core is row regular.Row regular means that the number of edges in each row is the same.Precise row regularity is not always achievable, because the number ofedges may not be a factor of the number of rows. However, it is alwayspossible to ensure that the row degrees differ by at most one. In viewof this, it is desirable that the degree 3 portion of the core be nearlyrow regular for all submatrices induced by the shortening. The submatrixwith k_(b,min) information columns may have the property that the degree3 portion of the core is nearly row regular. More generally, thesubmatrices with information columns k_(b,min)+i for i=0, 1, . . . ,k_(b,max)−k_(b,min) can be row regular (or mostly row regular). This mayprovide desirable performance of shortened base graphs.

In some cases, it may be desirable for general performance or errorfloor reasons to have some check irregularity in the degree 3 portion ofthe core. For example, it may be desirable to have one or more of thecheck nodes connected to a single punctured variable node to have amaximal number of degree 3 core edges. In the irregular case, theadditional core degree 3 nodes in the nesting sequence may have theiredges placed so as to preserve the desired irregularity. This cangenerally be achieved by having the additional degree 3 nodes connectedas in the regular case, i.e., so that differences in the degrees presentin the first member of the nested sequence are preserved across thesequence. This can be achieved by connecting the additional degree 3nodes in a way that is consistent with the regular case for somestarting values.

FIGS. 19-21A show example code families, in accordance with certainaspects of the present disclosure. The example code families are basedon the example tower of clustered liftings given by Z=2^(j){4,5,6,7}where the maximum of Z_(i+1)/Z_(i) is 5/4=1.25. The examples codefamilies in FIGS. 19, 20, and 21, use a PCM with (k_(b,min),k_(b,max))=(24,30), (16,20), and (8,10), respectively.

This example code family illustrated in FIG. 19 has (k_(b,min),k_(b,max))=(24,30). The bottom row in the graph 1900 is for the paritybit of the punctured nodes and is not a part of the degree 3 submatrixthat is desired to be row regular. The relevant submatrix for theexample code family, shown in the table 1900A in FIG. 19A, consists ofthe first six rows and columns 3 through 30 from the graph 1900. If thecode family is shortened to k_(b)=24, columns 30 through 25 are removedsuccessively. As seen in the table 1900A, each row in the submatrix hasentries that differ by at most one, so near regularity is achieved forall shortened base graphs.

FIG. 20 is graph 2000 showing the core of the another example codefamily. This code family has (k_(b,min), k_(b,max))=(16,20) and therelevant rows are the first eight rows. The corresponding shortenedtable of degrees is shown in FIG. 20A. As shown in table 2000A, near rowregularity is maintained.

FIG. 21 shows the core of yet another example code family. This codefamily has (k_(b,min), k_(b,max))=(8,10). In this case, the code familyincludes three HARQ extension bits. The first ten rows are the rows inwhich near row regularity of the degree portion (columns 3 through 10)is desired. The corresponding table of row degrees is as shown in FIG.21A. As shown in table 2100A, near row regularity is maintained.

In the base PCM, there may be two punctured nodes. The core encodingparity check nodes, for example, all core check nodes except the oneconnected to the two punctured nodes and a degree 1 variable node (e.g.,also referred to as a parity bit), have either one edge connected to thehigh degree punctured nodes or two such edges. Best performance may beachieved when the number of core degree 3 edges from the checks with asingle edge connected to the high degree punctured variable nodes isgenerally higher than the number of core degree three edges from thechecks with two edges connected to the high degree punctured variablenodes. This may be the case for all base matrices in a set of nestedbase matrices

The connectivity of the set of nested base matrices should be such that,for each base matrix in the nested sequence, the maximal number ofdegree three core edges from any core check node is found on a corecheck node with a single edge to the punctured variable nodes. Theaverage degree 3 core for a set of check nodes can be defined as theaverage of their degree 3 core degrees. Another way of characterizingthe preferred irregularity indicated by density evolution is that theaverage 3 three core degree of the check nodes with single edges to thehigh degree punctured nodes should be higher than the average degree 3core degree of the check nodes with two edges to the high degreepunctured nodes.

Tables 1800, 2200, and 2300, illustrated in FIGS. 18, 22, and 23,respectively, illustrate examples for the high rate case, medium ratecase, and low rate case, respectively. FIGS. 18A, 22A, and 23A aregraphs 1800A, 2200A, and 2300A, respectively, illustrating the core partof the PCM, having a lifting size value of 8, corresponding to thetables 1800, 2200, and 2300, respectively.

Example LDPC Code Family Selection for Encoding Based on DesiredTransmission Rate

As described in the sections above, fine granularity of blocklengths canbe achieved by shortening of lifted base parity check matrices (PCM)(also referred to as the base graph or base matrix). A higher-rate basegraph can be extended to a lower rate by adding hybrid automatic repeatrequest (HARQ) extension bits (e.g., IR-HARQ extension) to the basegraph. Performance can be achieved at all levels of HARQ extension. Itis therefore possible to design LDPC codes covering many code rates andblocklengths by starting with a single high-rate base matrix and addinga large HARQ extension. LDPC codes generated from a base graphstructure, including the HARQ extension, that can support code rates inthe range [r_(min), r_(max)] and blocklengths in the rangek_(b,min)·Z₁≦K≦k_(b,max)·Z_(m) may be referred to as a family of codes.The set of liftings in the code family may be a tower of clusteredliftings, as described above.

It may be desirable to use more than one family of LDPC codes forencoding information to be transmitted. Optimized HARQ extensions of thebase PCM may be of higher degree than the core PCM. Therefore, lowerrate codes formed from higher rate codes with HARQ extensions may bemore complex than core designs for those lower rates. In order to avoiddouble edges in the base graph, it may be undesirable for base graphsfor high rate codes to have few variable nodes, since the number ofcheck nodes is not few. For few variable nodes at high rates, the numberof check nodes is few. To achieve a low code rate, a relatively largenumber of extension bits may be required, which may be undesirable froman implementation standpoint where higher parallelism (i.e., larger Z)and a smaller base graph may be preferable.

Accordingly, techniques for using more than one family of LDPC codes aredesirable.

Techniques are provided herein for selecting a family of LDPC codes touse for encoding information to be transmitted based on a desired ratefor the transmission.

FIG. 24 is a flow diagram illustrating example operations 2400 forselecting a family of LDPC codes to use for encoding information, inaccordance with certain aspects of the present disclosure. Operations2400 may be performed by a transmitting device (e.g., BS 110 or a UE120). A transmission can be divided into a set of ranges of code rates(e.g., code rate regions) for the transmission. At 2402, thetransmitting device selects a base matrix from a nested set of basematrices, each base matrix for generating a family of low density paritycheck (LDPC) codes, the selection based on a comparison of a range ofcode rates supported by the family of LDPC codes and a range of coderates for the transmission. The base matrices may correspond todifferent first transmission rates and have an approximately equalnumber of base variables at full HARQ extension or achieve approximatelyequal lowest code rates. Different base matrices can be selected fordifferent ranges of code rates for the transmission. The base matricesmay be core base matrices corresponding to a highest code rate in thefamily of the code rates. Each family of LDPC codes may be associatedwith a set of lifting values k used to generate members of the familyfrom a base matrix. A base matrix associated with a family of LDPC codesthat supports a range of codes having a lowest maximum code rate in therange of code rates that is greater than a maximum code rate of therange of code rates for the transmission may be selected. At 2404, thetransmitting device encodes a set of information bits based on theselected families of LDPC codes to produce a code word. For example, theselected base matrix can be used to generate members of the family ofLDPC codes having code rates corresponding to the range of code rates.At 2406, the transmitting device transmits the code word over a wirelessmedium.

According to certain aspects, a collection of families may be used forencoding. As described in the section above, each family may include atower of clustered liftings and base graph designs that supportshortening.

According to certain aspects, a set of base graphs (corresponding to thecollection of families) can be used. The cores of the different basegraphs may have different starting rates. As described above, a familyincludes a base graph having a minimum of k_(b,min) information columnsand a maximum of k_(b,max) information columns and its extension forHARQ. The core refers to the highest-rate graph in that code family.

Referring back to the three example base graphs 1800, 2200, and 2300 forthe three example code families described in the preceding section,these three base graphs have near regularity in check node degrees withinformation bit shortening. In these example code families, the coreshave a number of parity checks equal to 7, 9, and 11, respectively, andk_(b,min) (k_(b,max)) values of 24 (30), 16 (20), and 8 (10),respectively. Each base graph has two high-degree punctured nodes. Thus,the starting rates for the three code families are 24/29((k_(b,min)=24)/(24 information bits+7 parity bits −2 puncturedbits=29), 16/23 ((k_(b,min)=16)/(16 information bits+9 parity bits−2punctured bits=23), and 8/19 ((k_(b,min)=8)/(8 information bits+11parity bits−2 punctured bits=19), respectively. Higher code rates can beachieved by puncturing core variable bits. For example, a code rate 8/9can be achieved with the first example code family by puncturing twobase degree 2 variable nodes, to achieve a 24/27 code rate (i.e., 8/9code rate) from the 24/29 code rate.

As described in the sections above, the core rate is defined as thehighest rate which can be supported by all k_(b,min)≦k_(b)≦k_(b,max) andis given by r_(max)=k_(b,min)/(k_(b,min)−p_(b)+c_(b,min)). Each of thebase graphs can be extended with HARQ extension parity bits. Forexample, the three example base graphs, mentioned in the paragraphabove, can be extended to 122 variable columns. In this case, theexample code family shown in FIG. 18 may support the highest code ratesin the range [1/4, 8/9], the example code family shown in FIG. 22 maysupport the second highest code rates in the range [1/6, 16/23], and theexample code family shown in FIG. 23 may support the lowest code ratesin the range [1/12, 8/19]. These rate regions overlap so that for someblocklengths and code rates, there will be multiple solutions. Sometimeseven a single code family may have multiple solutions.

Since lower rate cores may have better performance than thecorresponding code in a higher core rate code family, it may bedesirable to use the lowest rate code family for code rates startingbelow the core code rate of that code family. Even if the performance isnot better for the lower rate core, since the number of base variablenode is smaller, the lifting size Z will be larger for a given blocksize. Thus, more parallelism is available for the lower rate core. Inaddition, complexity, as measured by edge density in the Tanner graph,may be lower for the lower rate core.

FIG. 25 is a flow diagram illustrating example operations 2500 forwireless communications, in accordance with certain aspects of thepresent disclosure. Operations 2500 may be performed by a transmittingdevice (e.g., BS 110 or a UE 120). At 2502, the transmitting devicedetermines a plurality of transmission rate regions associated with atransmission rate to be used for transmitting information bits. At 2504,the transmitting device selects a family of lifted LDPC codes of a setof families of LDPC codes for encoding information bits for transmissionin each of the transmission rate regions. At 2506, the transmittingdevice encodes the information bits using at least one lifted LDPC codefrom the selected family of lifted LDPC codes t for transmission in eachrespective transmission rate region to produce one or more code words.At 2508, the transmitting device transmits the one or more code wordsover a (e.g., wireless) medium.

According to certain aspects, the desired transmission rate range (e.g.,for first transmission) can be divided into multiple parts or rateranges. For example, a desired rate range of [1/12, 8/9] can be dividedinto the following four parts or ranges: [1/12, 1/5]; [1/5, 2/5]; [2/5,2/3]; [2/3, 8/9]. For the part of the desired transmission rate rangecorresponding to the largest rates, in this example, [2/3, 8/9], theextended graph of the highest rate code family, in this example thefirst code family supporting the range [1/4, 8/9], can be selected toobtain codes for all first transmission rates in the range [2/3, 8/9].For the example desired transmission range [2/5, 2/3], the secondexample code family corresponding to the second largest rates, in thisexample, [1/6, 16/23], can be selected to obtain the codes. If the firsttransmission rate is below rate 2/5 then the lowest core rate codefamily would be used. Thus, for the example desired transmission ranges[1/12, 1/5] and [1/5, 2/5], the third example code family correspondingto the lowest rates, in this example, [1/12, 8/19], can be selected toobtain the codes.

Example Selection of LDPC Code from a Family of LDPC Codes for a DesiredTransmission Rate

As described in the sections above, a coding scheme can be used thatuses two or more LDPC families (i.e., multiple lifted base graphs withshortening and puncturing), where different LDPC families can be usedfor encoding information to be transmitted depending on the desired(starting) transmission rate (and other factors).

For a desired K (number of information bits) and N (number of code bitcolumns), there may be multiple solutions by varying the number of basegraph columns used, the value of the lifting, and the number ofshortened/punctured bits. As described in the section above, for a givenK, N, a family of LDPC codes may be selected that has a minimum andmaximum number of information columns denoted by k_(b,min) andk_(b,max). The supported lift sizes form a tower given by {Z₁, Z₂, . . ., Z_(m)}. Thus, for a desired K, N there could be multiple ways toconstruct the code by choosing k_(b,min)≦K≦k_(b,max) and usingshortening.

Accordingly, techniques for selecting a particular code from within afamily of codes for encoding information for a desired transmission rateare desirable.

According to certain aspects, among the possible solution, the LDPC thatuses minimum base information columns may be selected. In other words,the LDPC code that uses the largest lift size in the selected family ofliftings may be selected. This may allow a higher parallelism for thedesired K, N, resulting in larger throughputs. Alternatively, theperformance of the multiple codes may be predetermined (known), and thecode with the best performance can be selected for use.

Example Encoding Structure for Compactly Described LDPC Codes for LowError-Floor Using Different Cyclic Permutations on the Degree 3 ParityBit in the Accumulate Chain

As described above, quasi-cyclic lifted LDPC code can be constructed bylifting a base graph detailing the macro structure of the code (i.e.,the number of variable nodes and check nodes in the base graph and theirconnections) to obtain the final graph or final PCM. The base graph canbe lifted by copying the base graph Z times (i.e., the lifting sizes andinterconnecting the copies by a random permutation. The permutationsused are from the cyclic group of integers modulo the lift values.

LDPC code words may be considered a subgroup of the algebra ofpolynomials modulo x^(z)−1. The encoding problem may reduce to solving alinear system:

D(x)=M(x)C(x),

where M(x) is the square m x m submatrix of the m×n PCM (H), C(x) is thepart of the code word corresponding to the parity bits, and D(x) is thesyndrome obtained using the systematic bits. For example, in 802.11n,there is an accumulate chain of degree 2 parity bits terminated using adegree 3 parity bit. This is represented by the polynomial matrix shownbelow.

${M(x)} = \begin{bmatrix}x & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

For the entries in M(x), an all zero matrix is represented by a 0, anidentity matrix is represented by a 1, and x represents the identitymatrix cyclically shifted by x.

Encoding can be performed by multiplying M(x) with the vector [1 1 1 1 11] to obtain C₁(x)=[1 1 1 1 1 1] D(x). The first parity may then besolved for, followed by the rest of the parities using backsubstitution. An equivalent structure may be obtained by replacing thex,1,x sequence in the first column with any sequence xa, xb, xa as longas |a−b|=1. This equivalence may be exploited to obtain a transitionfrom this encoding scheme to the one outlined above that is consistentwith earlier described nested representations of towers of clusteredliftings.

The above encoding structure creates loops of degree 2 and size m withone degree 3 check node. In some cases, this encoding structure leads tohigh error-floors. Hence, it is desirable to modify this structure sothat deeper error floors may be achieved. In the case of LDPC families,such as described above, it may not be straightforward to provide asolution that supports the optimization of multiple liftings. Thus,aspects of the present disclosure provide techniques that allow foroptimization of multiple lifting simultaneously. This may involveintroducing a different permutation on the edges of a degree 3parity-bit in the encoding matrix.

Small loops in the lifted encoding structure may be avoided using anencoding submatrix in the form:

${M(x)} = \begin{bmatrix}x^{Z\text{/}4} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\x & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\1 & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

This structure, instead of having Z loops of size 6, has Z/4 loops ofsize 4*6=24.

If, M(x) is multiplied with the vector [1 1 1 1 1 1], the encodingequation Q(x) C₁(x)=[1 1 1 1 1 1]D(x) is obtained, whereQ(x)=1+x+x+x^(z/4). As can be seen, in order to solve for C₁(x), Q(x)needs to be inverted. A general property of binary polynomials P(x) isthat (P(x))²=P(x²). Thus, Q(x⁴)=x⁴=Q(x²)Q(x)Q(x), and the inverse ofQ(x) is given by x^(Z−4) Q(x²)Q(x). Unfortunately, this approach cannotbe used directly for multiple liftings since the exponent of x^(Z/4)depends on Z. The challenge is to find a similar solution that works formultiple Z.

To mimic the above construction, a solution may take the form of apolynomial Q(x)=1+x^(a)+x^(b), where it may be assumed that b>a, so thatfor some power of 2, given by h, Q(x^(h)) is a monomial modulo x^(Z)+1for several Z. In a particular case, aspects of the present disclosuremay focus on a particular tower of clustered values, an example of whichhas been described above, given by 2^(j){4,5,6,7}.

To reduce Q(x^(h))=1+x^(ha)x^(hb) to a monomial modulo x^(Z)+1, Z mustbe a factor of either ‘ha’, ‘hb’, or ‘hb−ha’. These three terms musthave a factor of 3, a factor of 5, and a factor of 7. Since ‘h’ is apower of 2, these primes are factors of ‘a’, ‘b’, or ‘b−a’. ‘a’ and ‘b’may be less than 2^(j)4. Since, in a particular scheme, all of thegraphs may be optimized using liftings less than 2^(j)4, it is helpfulin the optimization if the encoding matrix also satisfies thiscondition. In some cases, a desirable solution may be found when j is atleast 2. For example, one solution is a=5, b=12, since 12 has 3 as afactor and b−a=7. Then for h=4, Q(x⁴)=1+x²⁰+x⁴⁸, which is monomialmodulo x^(Z)+1 for Z in {16,20,24,28}. Because 12 is a factor of 4, h=4covers the case Z=16. An essentially equivalent solution is a=7 andb=12. Another solution of h=4 is (a,b)=(7,15). It can be verified thatthese are the only solutions for h=4. When h=8, other solutions arisesuch as (a,b)=(9,14) and (a,b)=(7,10) and (a,b)=(7,15).

According to certain aspects, for some choices of Z, a smaller ‘h’ maysuffice. For example, when (a,b)=(7,15), h=2 may be acceptable whenZ=16. Additionally, it should be noted that if x⁰+x^(a)+x^(b) is asolution, then so is x¹x^(a+1)+x^(b+1) for any 1 provided b+1<16. Ingeneral, the idea is to use a polynomial x¹(1+x^(a)+x^(b)) where, for‘h’ being some power of 2, at least one of ha, hb, or hb−ha has Z as afactor for Z in {16,20,24,28} and ‘b’ less than 16.

Given a solution (a,b) for Z in {16,20,24,28} with a given ‘h’, it isalso a solution for Z in 2^(j){16,20,24,28} with 2^(j)h. More generally,for k, at most j, (2^(k)a, 2^(k)b) is a solution with 2^(j−k)h. Aconvenient solution for the family Z=2^(j) {4,5,6,7} for j>1 is (2^(j−2)a, 2^(j−2) b) where (a,b) is a solution for the case j=2. For example,choosing (a,b)=(5,12) a solution so that Q(x⁴) is monomial for all Z inthe tower may be obtained.

With the above choice the encoding matrix for the set of Z given by{16,20,24,28} is:

${M(x)} = \begin{bmatrix}x^{5} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{12} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

and for j=3, {32,40,48,56}:

${M(x)} = \begin{bmatrix}x^{10} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{24} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

Multiplying by 2 is consistent with the nested representation of thetower of clustered liftings described earlier. Accordingly, followingthe encoding procedure described above may allow for optimization ofmultiple liftings simultaneously.

In general for j>1 and h=2^(j−2), the non-zero terms in the first columnfor the corresponding solution for the jth cluster are 1=x⁰,x^(5h), andx^(12h). This solution is consistent with the previously mentionednested strategy. The solution may not, however, extend to the case j=1thus the solution does not extend to the full tower of clusters in a waythat is consistent with the compressed representation of the liftingvalues associated to the tower of clustered lifting sizes.

The above change in the encoding structure is intended to lower errorfloor effects and is most valuable for the larger lifting sizes in thecluster. For smaller lifting values, the 802.11 encoding structure hasbeen found to be adequate. Thus it would be advantageous to have asolution that uses the 802.11 encoding structure for j=1 thattransitions to the above solution for j>1 in a way that is consistentwith the nested representation of the tower of lifting sizes. Such asolution is possible if the order of the terms in the first column isset appropriately and an encoding structure that is equivalent, but notequal to the 802.11 encoding structure, is used for j=1. In the case ofcompressed liftings with 2 independent bits per cluster a solution is asfollows. First, for j=2 the terms x⁰, x⁵, and x¹² should be put in adifferent order with x¹² occupying the middle position. In a 4-bitbinary representation the sequence 0, 12, 5 is 0000, 1100, 0101, so aj=1 solution, to be consistent with the nested lifting strategy with twoindependent bits per cluster, should take the form 0xx, 1xx, 0xx where xindicates an arbitrary bit.

A solution equivalent (up to relabeling of lifted nodes) to the 802.11encoding scheme is any sequence of the form a, b, a where |b−a|=1. Oneequivalent solution under the above constraint in 3-bit binaryrepresentation is 011, 100, 011, which as an integer sequence is 3, 4,3. Thus the solution for j=1 takes the form

${M(x)} = \begin{bmatrix}x^{3} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\x^{4} & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{3} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

And for j>1 the solution is:

${M(x)} = \begin{bmatrix}x^{5h} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\x^{12h} & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{0} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

where h=2^(j−2). This solution is consistent with the nestedrepresentation of the tower of clustered lifting values.

Example Encoding Structure for Compactly Described LDPC Codes for LowError-Floors Using Degree 3 Parity Bits

As previously noted, different cyclic permutations (i.e., differentlifting values k) on the degree 3 parity bit in the accumulate chain maybe used to obtain deep error-floors. In some cases, it may be desirableto achieve even deeper error-floor behavior than attainable with anaccumulate chain. For example, the accumulate chain can be shortened bypromoting one or more of the variable nodes in the accumulate chain to adegree-3 node by adding an additional edge to the variable node. Theadditional edge may be added in a way that facilitates simple encoding.

As described above, one way to reduce the effect of loops on decodingperformance is to add an extra edge in the encoding structure byconverting one of the degree 2 parity bits to a degree 3 parity bit. Thedegree 2 loops may converge faster to the correct values and, hence,eliminate the error-floor. It may be desirable to ensure ease ofencoding (e.g., simple, less complex, implementations) for the M(x)submatrix of the PCM.

Aspects of the present disclosure provide M(x) submatrix design thatprovides ease of encoding. The M(x) submatrix may have the form:

${M(x)} = \begin{bmatrix}x^{a} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & x^{\frac{Z}{4}} & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{b} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

M(x) may be multiplied by the vector [1, 1, 1, 1+x^(Z/4), 1+x^(Z/4),1+x^(Z/4)] to obtain Q(x)C(x), where Q(x)=x^(a)+(1+x^(Z/4))(1+x^(b)).Q(x⁴)=x^(4a); thus, multiplying Q(x) withQ(x²)Q(x)=Q(x²)(Q(x))²=Q(x⁴)=x^(4a) (e.g., by leveraging thecharacteristic 2 of the ground field). Thus, Q(x) may be invertedefficiently.

However, these techniques may not be straight forward when multiple(e.g., a tower) of clustered liftings is used. Accordingly, aspects ofthe present disclosure provide techniques for extending the construction(i.e., adding an additional edge in the base graph) for application to atower of clustered liftings. For example, a corresponding solution for atower of clustered liftings is provided (e.g., which is not dependent onthe lifting size Z).

An example tower of clustered liftings, as described above, is given by2^(j){4,5,6,7}. An example submatrix M(x) may have the following form:

${M(x)} = \begin{bmatrix}x^{a} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & x^{c} & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{b} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

M(x) may be left-multiplied by the vector [1, 1, 1, 1+x^(c), 1+x^(c),1+x^(c)] to obtain Q(x)C(x), where Q(x)=x^(a)+(1+x^(c))(1+x^(b)). For an‘h’ of a power of 2, Q(x^(h)) should be a monomial modulo x^(Z)+1 for alifting Z in the tower of clustered liftings 2^(j){4,5,6,7}. Forexample, for j=2 (i.e., Z={16,20,24,28}), Q(x^(h)) reduces to a monomialonly if (1+x^(hc))(1+x^(hb)) reduced to 0 modulo x^(Z)+1. Thus, thechoice of ‘a’ (i.e., in x^(a)) is arbitrary. The reduction to a monomialoccurs only if Z is a factor of hc or hb, or Z is a factor of hb−hc andalso a factor of hb+hc.

Some of the solutions described above may be used for the case ofmultiple liftings. To determine whether a solution is appropriate, thesolution may be checked against the condition that Z is a factor ofhb−hc and hb+hc. For example, the solution (5,12) does not carry overbecause, although 12−5 is a factor of 7, which was used to cover theZ=28 case, 12+5 is not a factor of 7. The solution (7,15) does carryover because the difference 15−7=8 is used only to cover the Z=16 case.If (c,b)=(7,15), Q(x)=x^(8a)+(1+x⁵⁶)(1+x¹²⁰), which is monomial modulox^(z)+1 for all Z in j=2 (i.e., {Z=16,20,24,28}). The solution may begeneralized for the tower of clustered Z as described above. Forexample, for the j=3 cluster (i.e., Z={32,40,48,56}), a factor of two inthe degree of the indeterminate x may be introduced. Thus, the resultingsubmatrix encoding structure is:

${M(x)} = \begin{bmatrix}x^{a} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & x^{2c} & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{2b} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

For each successive j the tower of clustered liftings, the exponent ofthe intermediate x is increased by a factor of 2.

In another example. For j>1 encoding structure with the additional edgecan be:

${M(x)} = \begin{bmatrix}x^{a} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & x^{15h} & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{7h} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

The value for “a” can be chosen consistent with the nested lifting valuerepresentation. For the j=1 cluster of liftings, the submatrix can be:

${M(x)} = \begin{bmatrix}x^{3} & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & x^{7} & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\1 & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\x^{3} & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

This M(x) supports the encoding techniques described above. For example,M(x) can be left-multiplied by the vector [1, 1, 1, 1+x³, 1+x³, 1+x³]which results in 0 for all columns except the first column. This givesQ(x)=x³+(1+x³)(1+x⁷)=1+x⁷+x¹⁰. Q(x⁴) is a monomial modulo x^(Z)−1 forj=1 (i.e., Z={8,10,12,14}). As long as a<8 is chosen for the case j=2,this is consistent with the nested representation of liftings with twoindependent bits per cluster.

According to certain aspects, following the encoding technique describedabove by introducing an additional edge and raising the exponentialpower of the intermediate ‘x’ by two may provide a lower error-floorwhile maintaining ease of the encoding procedure.

Example High Rate Code Design

In order to achieve very high rate codes while keeping base graphsrelatively small, and supporting HARQ extensions to lower rates, ahighest transmission rate can be achieved by puncturing of some of thedegree 2 nodes in the encoding structure. If the matrix below representsan 802.11n type encoding submatrix then the parity bits other than thefirst column are good candidates for puncturing.

${M(x)} = \begin{bmatrix}1 & 1 & 0 & 0 & 0 & 0 \\0 & 1 & 1 & 0 & 0 & 0 \\0 & 0 & 1 & 1 & 0 & 0 \\x & 0 & 0 & 1 & 1 & 0 \\0 & 0 & 0 & 0 & 1 & 1 \\1 & 0 & 0 & 0 & 0 & 1\end{bmatrix}$

In an exemplary design, shown in FIGS. 26 and 27, a core code of rate30/35 allows puncturing of the 2 rightmost parity bits in the encodingstructure to achieve a rate of 30/33. The exemplary design is also anested sequence of base graphs intended for a range of informationcolumns from 24 to 30. For each of these base graphs one or two of therightmost encoding parity bits may be punctured to achieve high ratecodes.

FIG. 26 is an example core 2600 of a lifted PCM having a lifting sizevalue of Z=8, in accordance with certain aspects of the presentdisclosure. In FIGS. 26 and 27, the first row provides the index for thecolumns, the second row indicates systematic bits (1) or parity bits(0), and the third row indicates transmitted bits (1) or punctured bits(0). As shown in FIG. 26, the first two columns are punctured variablenodes of degree 5 and 6 (not counting the parity bit edges). The firstsix parity checks (rows) (parity nodes) are the encoding rows. The firstparity check has a single edge to the punctured variable nodes and allother parity checks have two edges to punctured variable nodes. The codecorresponding to the lifted PCM illustrated in FIG. 26 is a rate 30/35code.

FIG. 27 is an example of the core 2600 illustrated in FIG. 26 with asingle edge removed, in accordance with certain aspects of the presentdisclosure. As shown in FIG. 27, a single edge has been removed, suchthat the punctured degrees are now 5 and 5 (e.g., rather than 5 and 6 asin FIG. 26). The fifth check node was chosen for the edge removalbecause it is the last two degree 2 variable nodes (i.e., the rightmosttwo columns) that get punctured, in right to left order, in order toachieve higher degree codes, as indicated in the third row above. Thecode corresponding to the core 2700 illustrated in FIG. 27 is a rate30/33 code. Puncturing a degree 2 variable node effectively merges theneighboring parity checks. Thus, puncturing a degree 2 variable nodeeffectively joins two parity checks to create a much higher degreesingle parity check.

For the highest rate exemplary design, which has six check nodes in thecore (not counting the check for the parity of the punctured informationvariable nodes), the best asymptotic performance may be achieved with apunctured node of degree 6 (not counting the edge used to form a parityof the two punctured nodes), that connects to each base parity check,and one of degree 5 that connects to 5 core parity checks. The oneparity check with a single edge connected to the degree 6 punctured nodeis the one that is relied on initiate correct decoding of the puncturednodes.

In the HARQ extensions, having two check nodes with only a single edgeto the punctured nodes may be desirable for good performance in thesmaller lifting graphs. Thus, the degree 6 punctured node may be reducedto a degree 5 punctured node to create one additional check node withonly a single edge to the punctured nodes, as shown in FIG. 27. Theimpact in asymptotic performance for the non-punctured case was found tobe quite small. However, if degree 2 parity bits are punctured, the lossmay be much more severe. The increased loss may be due to the effectivechange in the check node degrees. Assuming punctured nodes of degree 5and 6, such that there is only one core check node has a single edge tothe puncture with the others (5) having two edges to the puncturednodes, a punctured degree 2 variable node effectively merges two checksthe merged check has four edges to punctured nodes.

Merging the check with a single edge to punctured nodes may leave allchecks with more than one edge to punctured nodes. In that case, thedecoding may fail. By reducing the punctured node from degree 6 todegree 5, there may be a significant difference in whether the reducededge connects to one of the merged checks of one of the others. If it isone of the others, then after merging there is one check with four edgesto punctured nodes, one with two edges, and two with one edge. On theother hand, if it is one of the merged check nodes from which the edgeis removed, then after merging there is one check with three edges topunctured nodes, two with two edges, and one with one edge. From adecoding perspective, the latter case is much more similar to thesituation prior to the removal of the edge to reduce the punctured nodedegree and results in much better performance.

Thus, a very good solution can be achieved for the high rate case wheretwo checks belonging to the encoding structure have single edges to thepunctured node, by merging one of those checks to achieve higher rates.In other words, one of the checks with a single edge is connected to thedegree two variable node that will first be punctured to achieve higherrate. In the exemplary code, as many as two degree 2 variable nodes maybe punctured. It may be preferable that the two punctured two 2 variablenodes are adjacent in the encoding accumulate chain. After puncturingtwo degree 2 variable nodes there are three effectively merged checknodes. One of these should be one with a single edge to the puncturednodes. The other check with one edge to punctured nodes should remainunmerged for all puncturing.

Thus, one aspect of the invention is the placement of check nodes havingsingle edges to punctured variable nodes so that one is one of thosemerged when puncturing degree two variable nodes to achieve higher coderate and the other is not merged.

Example HARQ Extension Arrangement for Error-Floor Performance

The parity bits formed for the HARQ extension of a core graph can bedesigned using density evolution to choose the number of placement ofbits used to form a parity. Density evolution makes the choice so thatasymptotic performance of the structure is optimized. In particular,density evolution may function as if it were operating on an infinitelylarge graph with no loops. A finite LDPC graph may have loops. Theseloops may degrade performance in a number of ways. Small structures inthe LDPC graphs, called trapping sets or near code words, can lead toerror-floor failure events. The optimization performed by densityevolution may not consider trapping sets, because trapping sets arisefrom the loops in the finite graph. Consequently, the density evolutionoptimization of the HARQ parity bits can leave the solution vulnerableto error floors.

An PCM with HARQ extension has a structure as optimized by densityevolution, with lifting Z=8. This example is from the high rate family.The density evolution optimization may produce irregular HARQ extensionin that some degree three cores participate in many more HARQ extensionparities than others and for some participation in HARQ extension,parity may not occur until many parities have been added; while othersparticipate in the first few HARQ extension parities. For example, adegree 3 core node in certain columns (e.g., columns 17 and 18) of anexample PCM may have no participation in HARQ parities for a largenumber of the first HARQ parities. Similarly, certain other columns(e.g., column 26) in the example PCM may not participate in some HARQparities, although it may have an early HARQ parity participation.Certain degree 2 parity columns (e.g., columns 35 and 36) in the examplePCM may not participate in the HARQ parity equations for many of theearly parities.

This combination of variable nodes can lead to bad error floorperformance for a large number of the first 50 parity extensions. Forexample, these variable nodes all connect to the same three check nodes(e.g., rows 3, 4 and 5 in the example PCM). Thus, these variable nodestogether with the check nodes form a subgraph that is untouched by HARQextension bits for many bits in the extension. As HARQ extension bitsare added to the code the code rate lowers so the operating signal tonoise ratio (SNR) for the code becomes lower. Thus, any trapping sets inthe subgraph may become more problematic as the probability of failingon the trapping set increases with lowering SNR.

Density evolution optimization may result in selection of certain nodeshaving few HARQ extension bits, while certain others nodes have manyHARQ extension bits. In the degree 3 core, nodes with exactly the sameconnectivity to the check nodes may be selected to be the ones with thefewest early HARQ bits. From an error-floor perspective, however, thesubgraph of the nodes with the same connectivity may have relativelysmall trapping sets, which may lead to poor error floor performance.

This problem may be corrected. Although the density evolutionoptimization of the HARQ involves detailed knowledge of the nodeconnectivity, many of the choices of where to place HARQ edges may benearly arbitrary. Although the optimization results in selection of aparticular node, the selection of another node in its place may haveresult in little difference. Once some HARQ edges have been placed,additional edge decisions may be affected the by irregularity created byprevious edges and should not be altered to maintain performance. Thus,a swap between degree 3 nodes of their entire HARQ extension sequencemay be expected to have very little deleterious effect on the densityevolution predicted asymptotic performance while potentiallysignificantly improving the error floor. Similarly, the HARQ edgesequence of degree 2 parity nodes may be swapped without significantlyaffected the density evolution predicted asymptotic performance.

Swapping the HARQ sequence as suggested above can be guided by thefollowing considerations. Certain core degree 3 variable nodes may beselected to participate in relatively few HARQ extension parities. Thosevariable nodes, ideally, have little overlap in the check nodes so thattrapping sets including them would be relatively large, including somedegree 2 variable nodes and other degree 3 core variable nodes that dohave much participation in HARQ extension bits. In the particular caseof the high rate example given above, the last two degree 2 core paritybits can be punctured to achieve a high rate code. Thus, the code may beoptimized so that core trapping sets involving those degree 2 variablenodes may be relatively large. Thus, it may be preferable for thosedegree 2 nodes to be the ones with relatively small participation in theHARQ extension bits.

After swapping HARQ sequences, the HARQ lifting values may bereoptimized. For example, the HARQ parity sequence of certain nodes(e.g., nodes 15 and 17, the nodes 18 and 19, and the nodes 35 and 37)may be swapped. This arrangement may lead to much better error-floorperformance.

Thus, in graphs in which some degree 2 parity variable nodes may bepunctured, the node that get punctured first may be the that lastparticipates in the HARQ parity sequence. The degree 3 code nodes thathave longer initial periods during which they do not participate in theHARQ parity sequence should not connect to the same set of check nodes.Each should have at least one edge that connects to a check node notconnected to the others and they should not connect only to those checknodes connected to the degree 2 parity nodes having little earlyparticipation in the HARQ parity sequence. The above described swappingmay achieve these conditions and result in much better error floorperformance while retaining the previous good performance above theerror floor region.

Conclusion

The encoding techniques described herein for high performance, flexible,and compact LDPC codes may lead to improved processor performance. Forexample, the techniques may allow for a processor to efficiently encodeinformation of various blocklengths and code rates using good codes(e.g., having few loops). For example, a device, such as a processingsystem in BS 110 or UE 120 shown in FIG. 1, may encode and/or decodecode words according to aspects of the present disclosure more quicklyor more efficiently (e.g., consuming less power) than a device encodingand/or decoding code words according to previously known aspects.

The methods disclosed herein comprise one or more steps or actions forachieving the described method. The method steps and/or actions may beinterchanged with one another without departing from the scope of theclaims. In other words, unless a specific order of steps or actions isspecified, the order and/or use of specific steps and/or actions may bemodified without departing from the scope of the claims.

As used herein, the term “determining” encompasses a wide variety ofactions. For example, “determining” may include calculating, computing,processing, deriving, investigating, looking up (e.g., looking up in atable, a database or another data structure), ascertaining and the like.Also, “determining” may include receiving (e.g., receiving information),accessing (e.g., accessing data in a memory) and the like. Also,“determining” may include resolving, selecting, choosing, establishingand the like.

In some cases, rather than actually transmitting a frame, a device mayhave an interface to output a frame for transmission. For example, aprocessor may output a frame, via a bus interface, to an RF front endfor transmission. Similarly, rather than actually receiving a frame, adevice may have an interface to obtain a frame received from anotherdevice. For example, a processor may obtain (or receive) a frame, via abus interface, from an RF front end for transmission.

The various operations of methods described above may be performed byany suitable means capable of performing the corresponding functions.The means may include various hardware and/or software component(s)and/or module(s), including, but not limited to a circuit, anapplication specific integrated circuit (ASIC), or processor. Generally,where there are operations illustrated in figures, those operations mayhave corresponding counterpart means-plus-function components withsimilar numbering.

For example, means for encoding may include one or more processors, suchas the TX MIMO processor 430, Transmit processor 420, and/or theController/Processor 440 of the BS 110 illustrated in FIG. 4; the TXMIMO processor 466, Transmit Processor 464, and/or theController/Processor 480 of the UE 120 illustrated in FIG. 4; and/or theencoder 1102 of the encoder 1100 illustrated in FIG. 11. Means forpuncturing may comprise a processing system, which may include one ormore of processors of FIG. 4, and/or the puncturing module 1104 of theencoder 1100 illustrated in FIG. 11. Means for transmitting comprises atransmitter, which may include the Transmit processor 420, TX MIMOprocessor 430, modulator(s) 432 a-432 t, and/or the antenna(s) 434 a-434t of the BS 110 illustrated in FIG. 4; the Transmit processor 464, TXMIMO Processor 466, modulator(s) 454 a-454 r, and/or antenna(s) 452a-452 r of the UE 120 illustrated in FIG. 4; and/or the TX chain 1108and antenna 1110 of the encoder 1100 illustrated in FIG. 11.

The various illustrative logical blocks, modules and circuits describedin connection with the present disclosure may be implemented orperformed with a general purpose processor, a digital signal processor(DSP), an application specific integrated circuit (ASIC), a fieldprogrammable gate array (FPGA) or other programmable logic device (PLD),discrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.A general-purpose processor may be a microprocessor, but in thealternative, the processor may be any commercially available processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

If implemented in hardware, an example hardware configuration maycomprise a processing system in a wireless node. The processing systemmay be implemented with a bus architecture. The bus may include anynumber of interconnecting buses and bridges depending on the specificapplication of the processing system and the overall design constraints.The bus may link together various circuits including a processor,machine-readable media, and a bus interface. The bus interface may beused to connect a network adapter, among other things, to the processingsystem via the bus. The network adapter may be used to implement thesignal processing functions of the PHY layer. In the case of a wirelessnode (see FIG. 1), a user interface (e.g., keypad, display, mouse,joystick, etc.) may also be connected to the bus. The bus may also linkvarious other circuits such as timing sources, peripherals, voltageregulators, power management circuits, and the like, which are wellknown in the art, and therefore, will not be described any further. Theprocessor may be implemented with one or more general-purpose and/orspecial-purpose processors. Examples include microprocessors,microcontrollers, DSP processors, and other circuitry that can executesoftware. Those skilled in the art will recognize how best to implementthe described functionality for the processing system depending on theparticular application and the overall design constraints imposed on theoverall system.

If implemented in software, the functions may be stored or transmittedover as one or more instructions or code on a computer-readable medium.Software shall be construed broadly to mean instructions, data, or anycombination thereof, whether referred to as software, firmware,middleware, microcode, hardware description language, or otherwise.Computer-readable media include both computer storage media andcommunication media including any medium that facilitates transfer of acomputer program from one place to another. The processor may beresponsible for managing the bus and general processing, including theexecution of software modules stored on the machine-readable storagemedia. A computer-readable storage medium may be coupled to a processorsuch that the processor can read information from, and write informationto, the storage medium. In the alternative, the storage medium may beintegral to the processor. By way of example, the machine-readable mediamay include a transmission line, a carrier wave modulated by data,and/or a computer readable storage medium with instructions storedthereon separate from the wireless node, all of which may be accessed bythe processor through the bus interface. Alternatively, or in addition,the machine-readable media, or any portion thereof, may be integratedinto the processor, such as the case may be with cache and/or generalregister files. Examples of machine-readable storage media may include,by way of example, RAM (Random Access Memory), flash memory, ROM (ReadOnly Memory), PROM (Programmable Read-Only Memory), EPROM (ErasableProgrammable Read-Only Memory), EEPROM (Electrically ErasableProgrammable Read-Only Memory), registers, magnetic disks, opticaldisks, hard drives, or any other suitable storage medium, or anycombination thereof. The machine-readable media may be embodied in acomputer-program product.

A software module may comprise a single instruction, or manyinstructions, and may be distributed over several different codesegments, among different programs, and across multiple storage media.The computer-readable media may comprise a number of software modules.The software modules include instructions that, when executed by anapparatus such as a processor, cause the processing system to performvarious functions. The software modules may include a transmissionmodule and a receiving module. Each software module may reside in asingle storage device or be distributed across multiple storage devices.By way of example, a software module may be loaded into RAM from a harddrive when a triggering event occurs. During execution of the softwaremodule, the processor may load some of the instructions into cache toincrease access speed. One or more cache lines may then be loaded into ageneral register file for execution by the processor. When referring tothe functionality of a software module below, it will be understood thatsuch functionality is implemented by the processor when executinginstructions from that software module.

Also, any connection is properly termed a computer-readable medium. Forexample, if the software is transmitted from a website, server, or otherremote source using a coaxial cable, fiber optic cable, twisted pair,digital subscriber line (DSL), or wireless technologies such as infrared(IR), radio, and microwave, then the coaxial cable, fiber optic cable,twisted pair, DSL, or wireless technologies such as infrared, radio, andmicrowave are included in the definition of medium. Disk and disc, asused herein, include compact disc (CD), laser disc, optical disc,digital versatile disc (DVD), floppy disk, and Blu-ray® disc where disksusually reproduce data magnetically, while discs reproduce dataoptically with lasers. Thus, in some aspects computer-readable media maycomprise non-transitory computer-readable media (e.g., tangible media).In addition, for other aspects computer-readable media may comprisetransitory computer-readable media (e.g., a signal). Combinations of theabove should also be included within the scope of computer-readablemedia.

Thus, certain aspects may comprise a computer program product forperforming the operations presented herein. For example, such a computerprogram product may comprise a computer-readable medium havinginstructions stored (and/or encoded) thereon, the instructions beingexecutable by one or more processors to perform the operations describedherein.

Further, it should be appreciated that modules and/or other appropriatemeans for performing the methods and techniques described herein can bedownloaded and/or otherwise obtained by a wireless node and/or basestation as applicable. For example, such a device can be coupled to aserver to facilitate the transfer of means for performing the methodsdescribed herein. Alternatively, various methods described herein can beprovided via storage means (e.g., RAM, ROM, a physical storage mediumsuch as a compact disc (CD) or floppy disk, etc.), such that a wirelessnode and/or base station can obtain the various methods upon coupling orproviding the storage means to the device. Moreover, any other suitabletechnique for providing the methods and techniques described herein to adevice can be utilized.

It is to be understood that the claims are not limited to the preciseconfiguration and components illustrated above. Various modifications,changes and variations may be made in the arrangement, operation anddetails of the methods and apparatus described above without departingfrom the scope of the claims.

What is claimed is:
 1. A method for wireless communication, comprising:determining a plurality of transmission rate regions associated with atransmission rate to be used for transmitting information bits;selecting a family of lifted low-density parity-check (LDPC) codes of aset of families of lifted LDPC codes for encoding information bits foreach of the transmission rate regions; encoding information bits usingat least one lifted LDPC code from the selected family of lifted LDPCcodes for transmission in each respective transmission rate region toproduce one or more code words; and transmitting the one or more codewords over a medium.
 2. The method of claim 1, wherein each family oflifted LDPC codes is associated with a different base graph defininginformation bit columns and parity checks.
 3. The method of claim 1,wherein each family of lifted LDPC codes includes a tower of clusteredliftings, wherein the tower of clustered liftings comprises a pluralityof sets of clustered liftings, each set of clustered liftings includingliftings within a factor of each other, and the plurality of sets ofclustered liftings being exponentially spaced.
 4. The method of claim 1,wherein each family of lifted LDPC codes correspond to a different firsttransmission rate, and wherein the set of families of lifted LDPC codesare associated with base graphs having an approximately equal maximumnumber of base variable nodes at full hybrid automatic repeat request(HARQ) extension.
 5. The method of claim 1, wherein: each family oflifted LDPC codes comprises a set of lifted LDPC codes that support asame range of blocklengths and code rates, and selecting the family oflifted LDPC codes for encoding the information bits for transmission isbased, at least in part, on at least one of the supported range ofblocklengths or codes rates.
 6. The method of claim 5, wherein: therange of supported blocklengths is defined by a set of liftingsassociated with the family of lifted LDPC codes; and the range ofsupported code rates is defined by a highest code rate corresponding toa core graph obtained by puncturing a base graph associated with thefamily of lifted LDPC codes and a lowest code rate corresponding to anextended graph obtained by adding hybrid automatic repeat request (HARQ)extension bits to the base graph.
 7. The method of claim 6, whereinselecting the family of lifted LDPC codes for encoding the informationbits for transmission in each transmission rate region comprises:selecting the family of lifted LDPC codes that has a highest code ratethat is closest to a highest transmission rate of that transmission rateregion.
 8. The method of claim 7, wherein encoding the information bitsusing at least one lifted LDPC code from the selected family of liftedLDPC codes to encode the set of the information bits for transmission ineach respective transmission rate region comprises: for the highesttransmission rate in each transmission rate region, using the liftedLDPC code from the selected family of lifted LDPC codes that correspondsto the highest code rate of that family of lifted LDPC codes; and forother transmission rates in each rate region, using lifted LDPC codesfrom the selected family of lifted LDPC codes that correspond to lowercode rates of that family of LDPC codes obtained from the extended basegraph associated with the selected family of LDPC codes.
 9. The methodof claim 8, wherein encoding the information bits using at least onelifted LDPC code from the selected family of lifted LDPC codes to encodethe set of the information bits for transmission in each respectivetransmission rate region comprises: selecting the lifted LDPC code fromthe selected family of lifted LDPC codes further based on a lifting sizeassociated with lifted LDPC code.
 10. The method of claim 9, whereinselecting the lifted LDPC code comprises: for lifted LDPC codes in theselected family of lifted LDPC codes that each correspond to a samerate, selecting the lifted LDPC code that is associated with a largestlifting size.
 11. An apparatus for wireless communication, comprising:means for determining a plurality of transmission rate regionsassociated with a transmission rate to be used for transmittinginformation bits; means for selecting a family of lifted low-densityparity-check (LDPC) codes of a set of families of lifted LDPC codes forencoding information bits for each of the transmission rate regions;means for encoding information bits using at least one lifted LDPC codefrom the selected family of lifted LDPC codes for transmission in eachrespective transmission rate region to produce one or more code words;and means for transmitting the one or more code words over a medium. 12.The apparatus of claim 11, wherein each family of lifted LDPC codes isassociated with a different base graph defining information bit columnsand parity checks.
 13. The apparatus of claim 11, wherein each family oflifted LDPC codes includes a tower of clustered liftings, wherein thetower of clustered liftings comprises a plurality of sets of clusteredliftings, each set of clustered liftings including liftings within afactor of each other, and the plurality of sets of clustered liftingsbeing exponentially spaced.
 14. The apparatus of claim 11, wherein eachfamily of lifted LDPC codes correspond to a different first transmissionrate, and wherein the set of families of lifted LDPC codes areassociated with base graphs having an approximately equal maximum numberof base variable nodes at full hybrid automatic repeat request (HARQ)extension.
 15. The apparatus of claim 11, wherein: each family of liftedLDPC codes comprises a set of lifted LDPC codes that support a samerange of blocklengths and code rates, and selecting the family of liftedLDPC codes for encoding the information bits for transmission is based,at least in part, on at least one of the supported range of blocklengthsor codes rates.
 16. The apparatus of claim 15, wherein: the range ofsupported blocklengths is defined by a set of liftings associated withthe family of lifted LDPC codes; and the range of supported code ratesis defined by a highest code rate corresponding to a core graph obtainedby puncturing a base graph associated with the family of lifted LDPCcodes and a lowest code rate corresponding to an extended graph obtainedby adding hybrid automatic repeat request (HARQ) extension bits to thebase graph.
 17. The apparatus of claim 16, wherein means for selectingthe family of lifted LDPC codes for encoding the information bits fortransmission in each transmission rate region comprises: means forselecting the family of lifted LDPC codes that has a highest code ratethat is closest to a highest transmission rate of that transmission rateregion.
 18. The apparatus of claim 17, wherein means for encoding theinformation bits using at least one lifted LDPC code from the selectedfamily of lifted LDPC codes to encode the set of the information bitsfor transmission in each respective transmission rate region comprises:for the highest transmission rate in each transmission rate region,means for using the lifted LDPC code from the selected family of liftedLDPC codes that corresponds to the highest code rate of that family oflifted LDPC codes; and for other transmission rates in each rate region,means for using lifted LDPC codes from the selected family of liftedLDPC codes that correspond to lower code rates of that family of LDPCcodes obtained from the extended base graph associated with the selectedfamily of LDPC codes.
 19. The apparatus of claim 18, wherein means forencoding the information bits using at least one lifted LDPC code fromthe selected family of lifted LDPC codes to encode the set of theinformation bits for transmission in each respective transmission rateregion comprises: means for selecting the lifted LDPC code from theselected family of lifted LDPC codes further based on a lifting sizeassociated with lifted LDPC code.
 20. The apparatus of claim 19, whereinmeans for selecting the lifted LDPC code comprises: for lifted LDPCcodes in the selected family of lifted LDPC codes that each correspondto a same rate, means for selecting the lifted LDPC code that isassociated with a largest lifting size.
 21. An apparatus for wirelesscommunication, comprising: at least one processor coupled with a memoryand configured to: determine a plurality of transmission rate regionsassociated with a transmission rate to be used for transmittinginformation bits; select a family of lifted low-density parity-check(LDPC) codes of a set of families of lifted LDPC codes for encodinginformation bits for each of the transmission rate regions; encodeinformation bits using at least one lifted LDPC code from the selectedfamily of lifted LDPC codes for transmission in each respectivetransmission rate region to produce one or more code words; and atransmitter configured to transmit the one or more code words over amedium.
 22. The apparatus of claim 21, wherein each family of liftedLDPC codes is associated with a different base graph defininginformation bit columns and parity checks.
 23. The apparatus of claim21, wherein each family of lifted LDPC codes includes a tower ofclustered liftings, wherein the tower of clustered liftings comprises aplurality of sets of clustered liftings, each set of clustered liftingsincluding liftings within a factor of each other, and the plurality ofsets of clustered liftings being exponentially spaced.
 24. The apparatusof claim 21, wherein each family of lifted LDPC codes correspond to adifferent first transmission rate, and wherein the set of families oflifted LDPC codes are associated with base graphs having anapproximately equal maximum number of base variable nodes at full hybridautomatic repeat request (HARQ) extension.
 25. The apparatus of claim21, wherein: each family of lifted LDPC codes comprises a set of liftedLDPC codes that support a same range of blocklengths and code rates, andthe at least one processor is configured to select the family of liftedLDPC codes for encoding the information bits for transmission based, atleast in part, on at least one of the supported range of blocklengths orcodes rates.
 26. The apparatus of claim 21, wherein the at least oneprocessor is configured to encode the information bits by: for thehighest transmission rate in each transmission rate region, using thelifted LDPC code from the selected family of lifted LDPC codes thatcorresponds to the highest code rate of that family of lifted LDPCcodes; and for other transmission rates in each rate region, usinglifted LDPC codes from the selected family of lifted LDPC codes thatcorrespond to lower code rates of that family of LDPC codes obtainedfrom the extended base graph associated with the selected family of LDPCcodes.
 27. The apparatus of claim 21, wherein the at least one processoris configured to select the lifted LDPC code by: for lifted LDPC codesin the selected family of lifted LDPC codes that each correspond to asame rate, selecting the lifted LDPC code that is associated with alargest lifting size.
 28. A computer readable medium having computerexecutable code stored thereon for wireless communication, comprising:code for determining a plurality of transmission rate regions associatedwith a transmission rate to be used for transmitting information bits;code for selecting a family of lifted low-density parity-check (LDPC)codes of a set of families of lifted LDPC codes for encoding informationbits for each of the transmission rate regions; code for encodinginformation bits using at least one lifted LDPC code from the selectedfamily of lifted LDPC codes for transmission in each respectivetransmission rate region to produce one or more code words; and code fortransmitting the one or more code words over a medium.
 29. The computerreadable medium of claim 28, wherein each family of lifted LDPC codesincludes a tower of clustered liftings, wherein the tower of clusteredliftings comprises a plurality of sets of clustered liftings, each setof clustered liftings including liftings within a factor of each other,and the plurality of sets of clustered liftings being exponentiallyspaced.
 30. The computer readable medium of claim 28, furthercomprising: for the highest transmission rate in each transmission rateregion, code for using the lifted LDPC code from the selected family oflifted LDPC codes that corresponds to the highest code rate of thatfamily of lifted LDPC codes; and for other transmission rates in eachrate region, code for using lifted LDPC codes from the selected familyof lifted LDPC codes that correspond to lower code rates of that familyof LDPC codes obtained from the extended base graph associated with theselected family of LDPC codes.